diff --git a/.github/FUNDING.yml b/.github/FUNDING.yml
new file mode 100644
index 00000000..63dd55d2
--- /dev/null
+++ b/.github/FUNDING.yml
@@ -0,0 +1,3 @@
+# These are supported funding model platforms
+
+github: AndyMik90
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 80cc6e05..9e47df54 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -50,7 +50,7 @@ jobs:
PYTHONPATH: ${{ github.workspace }}/apps/backend
run: |
source .venv/bin/activate
- pytest ../../tests/ -v --cov=. --cov-report=xml --cov-report=term-missing --cov-fail-under=30
+ pytest ../../tests/ -v --cov=. --cov-report=xml --cov-report=term-missing
- name: Upload coverage reports
if: matrix.python-version == '3.12'
diff --git a/CLAUDE.md b/CLAUDE.md
index ed70a325..50fd53d5 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -4,7 +4,38 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
## Project Overview
-Auto Claude is a multi-agent autonomous coding framework that builds software through coordinated AI agent sessions. It uses the Claude Code SDK to run agents in isolated workspaces with security controls.
+Auto Claude is a multi-agent autonomous coding framework that builds software through coordinated AI agent sessions. It uses the Claude Agent SDK to run agents in isolated workspaces with security controls.
+
+**CRITICAL: All AI interactions use the Claude Agent SDK (`claude-agent-sdk` package), NOT the Anthropic API directly.**
+
+## Project Structure
+
+```
+autonomous-coding/
+├── apps/
+│ ├── backend/ # Python backend/CLI - ALL agent logic lives here
+│ │ ├── core/ # Client, auth, security
+│ │ ├── agents/ # Agent implementations
+│ │ ├── spec_agents/ # Spec creation agents
+│ │ ├── integrations/ # Graphiti, Linear, GitHub
+│ │ └── prompts/ # Agent system prompts
+│ └── frontend/ # Electron desktop UI
+├── guides/ # Documentation
+├── tests/ # Test suite
+└── scripts/ # Build and utility scripts
+```
+
+**When working with AI/LLM code:**
+- Look in `apps/backend/core/client.py` for the Claude SDK client setup
+- Reference `apps/backend/agents/` for working agent implementations
+- Check `apps/backend/spec_agents/` for spec creation agent examples
+- NEVER use `anthropic.Anthropic()` directly - always use `create_client()` from `core.client`
+
+**Frontend (Electron Desktop App):**
+- Built with Electron, React, TypeScript
+- AI agents can perform E2E testing using the Electron MCP server
+- When bug fixing or implementing features, use the Electron MCP server for automated testing
+- See "End-to-End Testing" section below for details
## Commands
@@ -133,19 +164,41 @@ See [RELEASE.md](RELEASE.md) for detailed release process documentation.
**Implementation (run.py → agent.py)** - Multi-session build:
1. Planner Agent creates subtask-based implementation plan
2. Coder Agent implements subtasks (can spawn subagents for parallel work)
-3. QA Reviewer validates acceptance criteria
-4. QA Fixer resolves issues in a loop
+3. QA Reviewer validates acceptance criteria (can perform E2E testing via Electron MCP for frontend changes)
+4. QA Fixer resolves issues in a loop (with E2E testing to verify fixes)
### Key Components (apps/backend/)
-- **client.py** - Claude SDK client with security hooks and tool permissions
-- **security.py** + **project_analyzer.py** - Dynamic command allowlisting based on detected project stack
-- **worktree.py** - Git worktree isolation for safe feature development
-- **memory.py** - File-based session memory (primary, always-available storage)
-- **graphiti_memory.py** - Graph-based cross-session memory with semantic search
-- **graphiti_providers.py** - Multi-provider factory for Graphiti (OpenAI, Anthropic, Azure, Ollama, Google AI)
+**Core Infrastructure:**
+- **core/client.py** - Claude Agent SDK client factory with security hooks and tool permissions
+- **core/security.py** - Dynamic command allowlisting based on detected project stack
+- **core/auth.py** - OAuth token management for Claude SDK authentication
+- **agents/** - Agent implementations (planner, coder, qa_reviewer, qa_fixer)
+- **spec_agents/** - Spec creation agents (gatherer, researcher, writer, critic)
+
+**Memory & Context:**
+- **integrations/graphiti/** - Graphiti memory system (mandatory)
+ - `queries_pkg/graphiti.py` - Main GraphitiMemory class
+ - `queries_pkg/client.py` - LadybugDB client wrapper
+ - `queries_pkg/queries.py` - Graph query operations
+ - `queries_pkg/search.py` - Semantic search logic
+ - `queries_pkg/schema.py` - Graph schema definitions
- **graphiti_config.py** - Configuration and validation for Graphiti integration
+- **graphiti_providers.py** - Multi-provider factory (OpenAI, Anthropic, Azure, Ollama, Google AI)
+- **agents/memory_manager.py** - Session memory orchestration
+
+**Workspace & Security:**
+- **cli/worktree.py** - Git worktree isolation for safe feature development
+- **context/project_analyzer.py** - Project stack detection for dynamic tooling
+- **auto_claude_tools.py** - Custom MCP tools integration
+
+**Integrations:**
- **linear_updater.py** - Optional Linear integration for progress tracking
+- **runners/github/** - GitHub Issues & PRs automation
+- **Electron MCP** - E2E testing integration for QA agents (Chrome DevTools Protocol)
+ - Enabled with `ELECTRON_MCP_ENABLED=true` in `.env`
+ - Allows QA agents to interact with running Electron app
+ - See "End-to-End Testing" section for details
### Agent Prompts (apps/backend/prompts/)
@@ -204,35 +257,208 @@ Three-layer defense:
Security profile cached in `.auto-claude-security.json`.
+### Claude Agent SDK Integration
+
+**CRITICAL: Auto Claude uses the Claude Agent SDK for ALL AI interactions. Never use the Anthropic API directly.**
+
+**Client Location:** `apps/backend/core/client.py`
+
+The `create_client()` function creates a configured `ClaudeSDKClient` instance with:
+- Multi-layered security (sandbox, permissions, security hooks)
+- Agent-specific tool permissions (planner, coder, qa_reviewer, qa_fixer)
+- Dynamic MCP server integration based on project capabilities
+- Extended thinking token budget control
+
+**Example usage in agents:**
+```python
+from core.client import create_client
+
+# Create SDK client (NOT raw Anthropic API client)
+client = create_client(
+ project_dir=project_dir,
+ spec_dir=spec_dir,
+ model="claude-sonnet-4-5-20250929",
+ agent_type="coder",
+ max_thinking_tokens=None # or 5000/10000/16000
+)
+
+# Run agent session
+response = client.create_agent_session(
+ name="coder-agent-session",
+ starting_message="Implement the authentication feature"
+)
+```
+
+**Why use the SDK:**
+- Pre-configured security (sandbox, allowlists, hooks)
+- Automatic MCP server integration (Context7, Linear, Graphiti, Electron, Puppeteer)
+- Tool permissions based on agent role
+- Session management and recovery
+- Unified API across all agent types
+
+**Where to find working examples:**
+- `apps/backend/agents/planner.py` - Planner agent
+- `apps/backend/agents/coder.py` - Coder agent
+- `apps/backend/agents/qa_reviewer.py` - QA reviewer
+- `apps/backend/agents/qa_fixer.py` - QA fixer
+- `apps/backend/spec_agents/` - Spec creation agents
+
### Memory System
-Dual-layer memory architecture:
+**Graphiti Memory (Mandatory)** - `integrations/graphiti/`
-**File-Based Memory (Primary)** - `memory.py`
-- Zero dependencies, always available
-- Human-readable files in `specs/XXX/memory/`
-- Session insights, patterns, gotchas, codebase map
+Auto Claude uses Graphiti as its primary memory system with embedded LadybugDB (no Docker required):
-**Graphiti Memory** - `graphiti_memory.py`
-- Graph database with semantic search (LadybugDB - embedded, no Docker)
-- Cross-session context retrieval
-- Multi-provider support:
+- **Graph database with semantic search** - Knowledge graph for cross-session context
+- **Session insights** - Patterns, gotchas, discoveries automatically extracted
+- **Multi-provider support:**
- LLM: OpenAI, Anthropic, Azure OpenAI, Ollama, Google AI (Gemini)
- Embedders: OpenAI, Voyage AI, Azure OpenAI, Ollama, Google AI
-- Configure with provider credentials in `.env.example`
+- **Modular architecture:** (`integrations/graphiti/queries_pkg/`)
+ - `graphiti.py` - Main GraphitiMemory class
+ - `client.py` - LadybugDB client wrapper
+ - `queries.py` - Graph query operations
+ - `search.py` - Semantic search logic
+ - `schema.py` - Graph schema definitions
-## Project Structure
+**Configuration:**
+- Set provider credentials in `apps/backend/.env` (see `.env.example`)
+- Required env vars: `GRAPHITI_ENABLED=true`, `ANTHROPIC_API_KEY` or other provider keys
+- Memory data stored in `.auto-claude/specs/XXX/graphiti/`
+**Usage in agents:**
+```python
+from integrations.graphiti.memory import get_graphiti_memory
+
+memory = get_graphiti_memory(spec_dir, project_dir)
+context = memory.get_context_for_session("Implementing feature X")
+memory.add_session_insight("Pattern: use React hooks for state")
```
-auto-claude/
-├── apps/
-│ ├── backend/ # Python backend/CLI (the framework code)
-│ └── frontend/ # Electron desktop UI
-├── guides/ # Documentation
-├── tests/ # Test suite
-└── scripts/ # Build and utility scripts
+
+## Development Guidelines
+
+### Frontend Internationalization (i18n)
+
+**CRITICAL: Always use i18n translation keys for all user-facing text in the frontend.**
+
+The frontend uses `react-i18next` for internationalization. All labels, buttons, messages, and user-facing text MUST use translation keys.
+
+**Translation file locations:**
+- `apps/frontend/src/shared/i18n/locales/en/*.json` - English translations
+- `apps/frontend/src/shared/i18n/locales/fr/*.json` - French translations
+
+**Translation namespaces:**
+- `common.json` - Shared labels, buttons, common terms
+- `navigation.json` - Sidebar navigation items, sections
+- `settings.json` - Settings page content
+- `dialogs.json` - Dialog boxes and modals
+- `tasks.json` - Task/spec related content
+- `onboarding.json` - Onboarding wizard content
+- `welcome.json` - Welcome screen content
+
+**Usage pattern:**
+```tsx
+import { useTranslation } from 'react-i18next';
+
+// In component
+const { t } = useTranslation(['navigation', 'common']);
+
+// Use translation keys, NOT hardcoded strings
+{t('navigation:items.githubPRs')} // ✅ CORRECT
+GitHub PRs // ❌ WRONG
```
+**When adding new UI text:**
+1. Add the translation key to ALL language files (at minimum: `en/*.json` and `fr/*.json`)
+2. Use `namespace:section.key` format (e.g., `navigation:items.githubPRs`)
+3. Never use hardcoded strings in JSX/TSX files
+
+### End-to-End Testing (Electron App)
+
+**IMPORTANT: When bug fixing or implementing new features in the frontend, AI agents can perform automated E2E testing using the Electron MCP server.**
+
+The Electron MCP server allows QA agents to interact with the running Electron app via Chrome DevTools Protocol:
+
+**Setup:**
+1. Start the Electron app with remote debugging enabled:
+ ```bash
+ npm run dev # Already configured with --remote-debugging-port=9222
+ ```
+
+2. Enable Electron MCP in `apps/backend/.env`:
+ ```bash
+ ELECTRON_MCP_ENABLED=true
+ ELECTRON_DEBUG_PORT=9222 # Default port
+ ```
+
+**Available Testing Capabilities:**
+
+QA agents (`qa_reviewer` and `qa_fixer`) automatically get access to Electron MCP tools:
+
+1. **Window Management**
+ - `mcp__electron__get_electron_window_info` - Get info about running windows
+ - `mcp__electron__take_screenshot` - Capture screenshots for visual verification
+
+2. **UI Interaction**
+ - `mcp__electron__send_command_to_electron` with commands:
+ - `click_by_text` - Click buttons/links by visible text
+ - `click_by_selector` - Click elements by CSS selector
+ - `fill_input` - Fill form fields by placeholder or selector
+ - `select_option` - Select dropdown options
+ - `send_keyboard_shortcut` - Send keyboard shortcuts (Enter, Ctrl+N, etc.)
+ - `navigate_to_hash` - Navigate to hash routes (#settings, #create, etc.)
+
+3. **Page Inspection**
+ - `get_page_structure` - Get organized overview of page elements
+ - `debug_elements` - Get debugging info about buttons and forms
+ - `verify_form_state` - Check form state and validation
+ - `eval` - Execute custom JavaScript code
+
+4. **Logging**
+ - `mcp__electron__read_electron_logs` - Read console logs for debugging
+
+**Example E2E Test Flow:**
+
+```python
+# 1. Agent takes screenshot to see current state
+agent: "Take a screenshot to see the current UI"
+# Uses: mcp__electron__take_screenshot
+
+# 2. Agent inspects page structure
+agent: "Get page structure to find available buttons"
+# Uses: mcp__electron__send_command_to_electron (command: "get_page_structure")
+
+# 3. Agent clicks a button to navigate
+agent: "Click the 'Create New Spec' button"
+# Uses: mcp__electron__send_command_to_electron (command: "click_by_text", args: {text: "Create New Spec"})
+
+# 4. Agent fills out a form
+agent: "Fill the task description field"
+# Uses: mcp__electron__send_command_to_electron (command: "fill_input", args: {placeholder: "Describe your task", value: "Add login feature"})
+
+# 5. Agent submits and verifies
+agent: "Click Submit and verify success"
+# Uses: click_by_text → take_screenshot → verify result
+```
+
+**When to Use E2E Testing:**
+
+- **Bug Fixes**: Reproduce the bug, apply fix, verify it's resolved
+- **New Features**: Implement feature, test the UI flow end-to-end
+- **UI Changes**: Verify visual changes and interactions work correctly
+- **Form Validation**: Test form submission, validation, error handling
+
+**Configuration in `core/client.py`:**
+
+The client automatically enables Electron MCP tools for QA agents when:
+- Project is detected as Electron (`is_electron` capability)
+- `ELECTRON_MCP_ENABLED=true` is set
+- Agent type is `qa_reviewer` or `qa_fixer`
+
+**Note:** Screenshots are automatically compressed (1280x720, quality 60, JPEG) to stay under Claude SDK's 1MB JSON message buffer limit.
+
+## Running the Application
+
**As a standalone CLI tool**:
```bash
cd apps/backend
@@ -242,7 +468,14 @@ python run.py --spec 001
**With the Electron frontend**:
```bash
npm start # Build and run desktop app
-npm run dev # Run in development mode
+npm run dev # Run in development mode (includes --remote-debugging-port=9222 for E2E testing)
```
-- `.auto-claude/specs/` - Per-project data (specs, plans, QA reports) - gitignored
+**For E2E Testing with QA Agents:**
+1. Start the Electron app: `npm run dev`
+2. Enable Electron MCP in `apps/backend/.env`: `ELECTRON_MCP_ENABLED=true`
+3. Run QA: `python run.py --spec 001 --qa`
+4. QA agents will automatically interact with the running app for testing
+
+**Project data storage:**
+- `.auto-claude/specs/` - Per-project data (specs, plans, QA reports, memory) - gitignored
diff --git a/README.md b/README.md
index d5234258..6174a26d 100644
--- a/README.md
+++ b/README.md
@@ -4,7 +4,7 @@

-[](https://github.com/AndyMik90/Auto-Claude/releases/latest)
+[](https://github.com/AndyMik90/Auto-Claude/releases/latest)
[](./agpl-3.0.txt)
[](https://discord.gg/KCXaPBr4Dj)
[](https://github.com/AndyMik90/Auto-Claude/actions)
@@ -17,11 +17,11 @@ Get the latest pre-built release for your platform:
| Platform | Download | Notes |
|----------|----------|-------|
-| **Windows** | [Auto-Claude-2.7.1.exe](https://github.com/AndyMik90/Auto-Claude/releases/latest) | Installer (NSIS) |
-| **macOS (Apple Silicon)** | [Auto-Claude-2.7.1-arm64.dmg](https://github.com/AndyMik90/Auto-Claude/releases/latest) | M1/M2/M3 Macs |
-| **macOS (Intel)** | [Auto-Claude-2.7.1-x64.dmg](https://github.com/AndyMik90/Auto-Claude/releases/latest) | Intel Macs |
-| **Linux** | [Auto-Claude-2.7.1.AppImage](https://github.com/AndyMik90/Auto-Claude/releases/latest) | Universal |
-| **Linux (Debian)** | [Auto-Claude-2.7.1.deb](https://github.com/AndyMik90/Auto-Claude/releases/latest) | Ubuntu/Debian |
+| **Windows** | [Auto-Claude-2.7.2.exe](https://github.com/AndyMik90/Auto-Claude/releases/latest) | Installer (NSIS) |
+| **macOS (Apple Silicon)** | [Auto-Claude-2.7.2-arm64.dmg](https://github.com/AndyMik90/Auto-Claude/releases/latest) | M1/M2/M3 Macs |
+| **macOS (Intel)** | [Auto-Claude-2.7.2-x64.dmg](https://github.com/AndyMik90/Auto-Claude/releases/latest) | Intel Macs |
+| **Linux** | [Auto-Claude-2.7.2.AppImage](https://github.com/AndyMik90/Auto-Claude/releases/latest) | Universal |
+| **Linux (Debian)** | [Auto-Claude-2.7.2.deb](https://github.com/AndyMik90/Auto-Claude/releases/latest) | Ubuntu/Debian |
> All releases include SHA256 checksums and VirusTotal scan results for security verification.
diff --git a/apps/backend/agents/tools_pkg/permissions.py b/apps/backend/agents/tools_pkg/permissions.py
index 67ef6c79..ee3994c4 100644
--- a/apps/backend/agents/tools_pkg/permissions.py
+++ b/apps/backend/agents/tools_pkg/permissions.py
@@ -77,6 +77,12 @@ def get_allowed_tools(
TOOL_GET_SESSION_CONTEXT,
],
},
+ "pr_reviewer": {
+ # PR reviewers can ONLY read - no bash, no edits, no writes
+ # This prevents the agent from switching branches or making changes
+ "base": BASE_READ_TOOLS,
+ "auto_claude": [], # No auto-claude tools needed for PR review
+ },
"qa_fixer": {
"base": BASE_READ_TOOLS + BASE_WRITE_TOOLS,
"auto_claude": [
diff --git a/apps/backend/prompts/github/duplicate_detector.md b/apps/backend/prompts/github/duplicate_detector.md
new file mode 100644
index 00000000..fa509b41
--- /dev/null
+++ b/apps/backend/prompts/github/duplicate_detector.md
@@ -0,0 +1,90 @@
+# Duplicate Issue Detector
+
+You are a duplicate issue detection specialist. Your task is to compare a target issue against a list of existing issues and determine if it's a duplicate.
+
+## Detection Strategy
+
+### Semantic Similarity Checks
+1. **Core problem matching**: Same underlying issue, different wording
+2. **Error signature matching**: Same stack traces, error messages
+3. **Feature request overlap**: Same functionality requested
+4. **Symptom matching**: Same symptoms, possibly different root cause
+
+### Similarity Indicators
+
+**Strong indicators (weight: high)**
+- Identical error messages
+- Same stack trace patterns
+- Same steps to reproduce
+- Same affected component
+
+**Moderate indicators (weight: medium)**
+- Similar description of the problem
+- Same area of functionality
+- Same user-facing symptoms
+- Related keywords in title
+
+**Weak indicators (weight: low)**
+- Same labels/tags
+- Same author (not reliable)
+- Similar time of submission
+
+## Comparison Process
+
+1. **Title Analysis**: Compare titles for semantic similarity
+2. **Description Analysis**: Compare problem descriptions
+3. **Technical Details**: Match error messages, stack traces
+4. **Context Analysis**: Same component/feature area
+5. **Comments Review**: Check if someone already mentioned similarity
+
+## Output Format
+
+For each potential duplicate, provide:
+
+```json
+{
+ "is_duplicate": true,
+ "duplicate_of": 123,
+ "confidence": 0.87,
+ "similarity_type": "same_error",
+ "explanation": "Both issues describe the same authentication timeout error occurring after 30 seconds of inactivity. The stack traces in both issues point to the same SessionManager.validateToken() method.",
+ "key_similarities": [
+ "Identical error: 'Session expired unexpectedly'",
+ "Same component: authentication module",
+ "Same trigger: 30-second timeout"
+ ],
+ "key_differences": [
+ "Different browser (Chrome vs Firefox)",
+ "Different user account types"
+ ]
+}
+```
+
+## Confidence Thresholds
+
+- **90%+**: Almost certainly duplicate, strong evidence
+- **80-89%**: Likely duplicate, needs quick verification
+- **70-79%**: Possibly duplicate, needs review
+- **60-69%**: Related but may be distinct issues
+- **<60%**: Not a duplicate
+
+## Important Guidelines
+
+1. **Err on the side of caution**: Only flag high-confidence duplicates
+2. **Consider nuance**: Same symptom doesn't always mean same issue
+3. **Check closed issues**: A "duplicate" might reference a closed issue
+4. **Version matters**: Same issue in different versions might not be duplicate
+5. **Platform specifics**: Platform-specific issues are usually distinct
+
+## Edge Cases
+
+### Not Duplicates Despite Similarity
+- Same feature, different implementation suggestions
+- Same error, different root cause
+- Same area, but distinct bugs
+- General vs specific version of request
+
+### Duplicates Despite Differences
+- Same bug, different reproduction steps
+- Same error message, different contexts
+- Same feature request, different justifications
diff --git a/apps/backend/prompts/github/issue_analyzer.md b/apps/backend/prompts/github/issue_analyzer.md
new file mode 100644
index 00000000..bcfe54d3
--- /dev/null
+++ b/apps/backend/prompts/github/issue_analyzer.md
@@ -0,0 +1,112 @@
+# Issue Analyzer for Auto-Fix
+
+You are an issue analysis specialist preparing a GitHub issue for automatic fixing. Your task is to extract structured requirements from the issue that can be used to create a development spec.
+
+## Analysis Goals
+
+1. **Understand the request**: What is the user actually asking for?
+2. **Identify scope**: What files/components are affected?
+3. **Define acceptance criteria**: How do we know it's fixed?
+4. **Assess complexity**: How much work is this?
+5. **Identify risks**: What could go wrong?
+
+## Issue Types
+
+### Bug Report Analysis
+Extract:
+- Current behavior (what's broken)
+- Expected behavior (what should happen)
+- Reproduction steps
+- Affected components
+- Environment details
+- Error messages/logs
+
+### Feature Request Analysis
+Extract:
+- Requested functionality
+- Use case/motivation
+- Acceptance criteria
+- UI/UX requirements
+- API changes needed
+- Breaking changes
+
+### Documentation Issue Analysis
+Extract:
+- What's missing/wrong
+- Affected docs
+- Target audience
+- Examples needed
+
+## Output Format
+
+```json
+{
+ "issue_type": "bug",
+ "title": "Concise task title",
+ "summary": "One paragraph summary of what needs to be done",
+ "requirements": [
+ "Fix the authentication timeout after 30 seconds",
+ "Ensure sessions persist correctly",
+ "Add retry logic for failed auth attempts"
+ ],
+ "acceptance_criteria": [
+ "User sessions remain valid for configured duration",
+ "Auth timeout errors no longer occur",
+ "Existing tests pass"
+ ],
+ "affected_areas": [
+ "src/auth/session.ts",
+ "src/middleware/auth.ts"
+ ],
+ "complexity": "standard",
+ "estimated_subtasks": 3,
+ "risks": [
+ "May affect existing session handling",
+ "Need to verify backwards compatibility"
+ ],
+ "needs_clarification": [],
+ "ready_for_spec": true
+}
+```
+
+## Complexity Levels
+
+- **simple**: Single file change, clear fix, < 1 hour
+- **standard**: Multiple files, moderate changes, 1-4 hours
+- **complex**: Architectural changes, many files, > 4 hours
+
+## Readiness Check
+
+Mark `ready_for_spec: true` only if:
+1. Clear understanding of what's needed
+2. Acceptance criteria can be defined
+3. Scope is reasonably bounded
+4. No blocking questions
+
+Mark `ready_for_spec: false` if:
+1. Requirements are ambiguous
+2. Multiple interpretations possible
+3. Missing critical information
+4. Scope is unbounded
+
+## Clarification Questions
+
+When not ready, populate `needs_clarification` with specific questions:
+```json
+{
+ "needs_clarification": [
+ "Should the timeout be configurable or hardcoded?",
+ "Does this need to work for both web and API clients?",
+ "Are there any backwards compatibility concerns?"
+ ],
+ "ready_for_spec": false
+}
+```
+
+## Guidelines
+
+1. **Be specific**: Generic requirements are unhelpful
+2. **Be realistic**: Don't promise more than the issue asks
+3. **Consider edge cases**: Think about what could go wrong
+4. **Identify dependencies**: Note if other work is needed first
+5. **Keep scope focused**: Flag feature creep for separate issues
diff --git a/apps/backend/prompts/github/issue_triager.md b/apps/backend/prompts/github/issue_triager.md
new file mode 100644
index 00000000..4fb2cf89
--- /dev/null
+++ b/apps/backend/prompts/github/issue_triager.md
@@ -0,0 +1,199 @@
+# Issue Triage Agent
+
+You are an expert issue triage assistant. Your goal is to classify GitHub issues, detect problems (duplicates, spam, feature creep), and suggest appropriate labels.
+
+## Classification Categories
+
+### Primary Categories
+- **bug**: Something is broken or not working as expected
+- **feature**: New functionality request
+- **documentation**: Docs improvements, corrections, or additions
+- **question**: User needs help or clarification
+- **duplicate**: Issue duplicates an existing issue
+- **spam**: Promotional content, gibberish, or abuse
+- **feature_creep**: Multiple unrelated requests bundled together
+
+## Detection Criteria
+
+### Duplicate Detection
+Consider an issue a duplicate if:
+- Same core problem described differently
+- Same feature request with different wording
+- Same question asked multiple ways
+- Similar stack traces or error messages
+- **Confidence threshold: 80%+**
+
+When detecting duplicates:
+1. Identify the original issue number
+2. Explain the similarity clearly
+3. Suggest closing with a link to the original
+
+### Spam Detection
+Flag as spam if:
+- Promotional content or advertising
+- Random characters or gibberish
+- Content unrelated to the project
+- Abusive or offensive language
+- Mass-submitted template content
+- **Confidence threshold: 75%+**
+
+When detecting spam:
+1. Don't engage with the content
+2. Recommend the `triage:needs-review` label
+3. Do not recommend auto-close (human decision)
+
+### Feature Creep Detection
+Flag as feature creep if:
+- Multiple unrelated features in one issue
+- Scope too large for a single issue
+- Mixing bugs with feature requests
+- Requesting entire systems/overhauls
+- **Confidence threshold: 70%+**
+
+When detecting feature creep:
+1. Identify the separate concerns
+2. Suggest how to break down the issue
+3. Add `triage:needs-breakdown` label
+
+## Priority Assessment
+
+### High Priority
+- Security vulnerabilities
+- Data loss potential
+- Breaks core functionality
+- Affects many users
+- Regression from previous version
+
+### Medium Priority
+- Feature requests with clear use case
+- Non-critical bugs
+- Performance issues
+- UX improvements
+
+### Low Priority
+- Minor enhancements
+- Edge cases
+- Cosmetic issues
+- "Nice to have" features
+
+## Label Taxonomy
+
+### Type Labels
+- `type:bug` - Bug report
+- `type:feature` - Feature request
+- `type:docs` - Documentation
+- `type:question` - Question or support
+
+### Priority Labels
+- `priority:high` - Urgent/important
+- `priority:medium` - Normal priority
+- `priority:low` - Nice to have
+
+### Triage Labels
+- `triage:potential-duplicate` - May be duplicate (needs human review)
+- `triage:needs-review` - Needs human review (spam/quality)
+- `triage:needs-breakdown` - Feature creep, needs splitting
+- `triage:needs-info` - Missing information
+
+### Component Labels (if applicable)
+- `component:frontend` - Frontend/UI related
+- `component:backend` - Backend/API related
+- `component:cli` - CLI related
+- `component:docs` - Documentation related
+
+### Platform Labels (if applicable)
+- `platform:windows`
+- `platform:macos`
+- `platform:linux`
+
+## Output Format
+
+Output a single JSON object:
+
+```json
+{
+ "category": "bug",
+ "confidence": 0.92,
+ "priority": "high",
+ "labels_to_add": ["type:bug", "priority:high", "component:backend"],
+ "labels_to_remove": [],
+ "is_duplicate": false,
+ "duplicate_of": null,
+ "is_spam": false,
+ "is_feature_creep": false,
+ "suggested_breakdown": [],
+ "comment": null
+}
+```
+
+### When Duplicate
+```json
+{
+ "category": "duplicate",
+ "confidence": 0.85,
+ "priority": "low",
+ "labels_to_add": ["triage:potential-duplicate"],
+ "labels_to_remove": [],
+ "is_duplicate": true,
+ "duplicate_of": 123,
+ "is_spam": false,
+ "is_feature_creep": false,
+ "suggested_breakdown": [],
+ "comment": "This appears to be a duplicate of #123 which addresses the same authentication timeout issue."
+}
+```
+
+### When Feature Creep
+```json
+{
+ "category": "feature_creep",
+ "confidence": 0.78,
+ "priority": "medium",
+ "labels_to_add": ["triage:needs-breakdown", "type:feature"],
+ "labels_to_remove": [],
+ "is_duplicate": false,
+ "duplicate_of": null,
+ "is_spam": false,
+ "is_feature_creep": true,
+ "suggested_breakdown": [
+ "Issue 1: Add dark mode support",
+ "Issue 2: Implement custom themes",
+ "Issue 3: Add color picker for accent colors"
+ ],
+ "comment": "This issue contains multiple distinct feature requests. Consider splitting into separate issues for better tracking."
+}
+```
+
+### When Spam
+```json
+{
+ "category": "spam",
+ "confidence": 0.95,
+ "priority": "low",
+ "labels_to_add": ["triage:needs-review"],
+ "labels_to_remove": [],
+ "is_duplicate": false,
+ "duplicate_of": null,
+ "is_spam": true,
+ "is_feature_creep": false,
+ "suggested_breakdown": [],
+ "comment": null
+}
+```
+
+## Guidelines
+
+1. **Be conservative**: When in doubt, don't flag as duplicate/spam
+2. **Provide reasoning**: Explain why you made classification decisions
+3. **Consider context**: New contributors may write unclear issues
+4. **Human in the loop**: Flag for review, don't auto-close
+5. **Be helpful**: If missing info, suggest what's needed
+6. **Cross-reference**: Check potential duplicates list carefully
+
+## Important Notes
+
+- Never suggest closing issues automatically
+- Labels are suggestions, not automatic applications
+- Comment field is optional - only add if truly helpful
+- Confidence should reflect genuine certainty (0.0-1.0)
+- When uncertain, use `triage:needs-review` label
diff --git a/apps/backend/prompts/github/pr_ai_triage.md b/apps/backend/prompts/github/pr_ai_triage.md
new file mode 100644
index 00000000..f13cf415
--- /dev/null
+++ b/apps/backend/prompts/github/pr_ai_triage.md
@@ -0,0 +1,183 @@
+# AI Comment Triage Agent
+
+## Your Role
+
+You are a senior engineer triaging comments left by **other AI code review tools** on this PR. Your job is to:
+
+1. **Verify each AI comment** - Is this a genuine issue or a false positive?
+2. **Assign a verdict** - Should the developer address this or ignore it?
+3. **Provide reasoning** - Explain why you agree or disagree with the AI's assessment
+4. **Draft a response** - Craft a helpful reply to post on the PR
+
+## Why This Matters
+
+AI code review tools (CodeRabbit, Cursor, Greptile, Copilot, etc.) are helpful but have high false positive rates (60-80% industry average). Developers waste time addressing non-issues. Your job is to:
+
+- **Amplify genuine issues** that the AI correctly identified
+- **Dismiss false positives** so developers can focus on real problems
+- **Add context** the AI may have missed (codebase conventions, intent, etc.)
+
+## Verdict Categories
+
+### CRITICAL
+The AI found a genuine, important issue that **must be addressed before merge**.
+
+Use when:
+- AI correctly identified a security vulnerability
+- AI found a real bug that will cause production issues
+- AI spotted a breaking change the author missed
+- The issue is verified and has real impact
+
+### IMPORTANT
+The AI found a valid issue that **should be addressed**.
+
+Use when:
+- AI found a legitimate code quality concern
+- The suggestion would meaningfully improve the code
+- It's a valid point but not blocking merge
+- Test coverage or documentation gaps are real
+
+### NICE_TO_HAVE
+The AI's suggestion is valid but **optional**.
+
+Use when:
+- AI suggests a refactor that would improve code but isn't necessary
+- Performance optimization that's not critical
+- Style improvements beyond project conventions
+- Valid suggestion but low priority
+
+### TRIVIAL
+The AI's comment is **not worth addressing**.
+
+Use when:
+- Style/formatting preferences that don't match project conventions
+- Overly pedantic suggestions (variable naming micro-preferences)
+- Suggestions that would add complexity without clear benefit
+- Comment is technically correct but practically irrelevant
+
+### FALSE_POSITIVE
+The AI is **wrong** about this.
+
+Use when:
+- AI misunderstood the code's intent
+- AI flagged a pattern that is intentional and correct
+- AI suggested a fix that would introduce bugs
+- AI missed context that makes the "issue" not an issue
+- AI duplicated another tool's comment
+
+## Evaluation Framework
+
+For each AI comment, analyze:
+
+### 1. Is the issue real?
+- Does the AI correctly understand what the code does?
+- Is there actually a problem, or is this working as intended?
+- Did the AI miss important context (comments, related code, conventions)?
+
+### 2. What's the actual severity?
+- AI tools often over-classify severity (e.g., "critical" for style issues)
+- Consider: What happens if this isn't fixed?
+- Is this a production risk or a minor annoyance?
+
+### 3. Is the fix correct?
+- Would the AI's suggested fix actually work?
+- Does it follow the project's patterns and conventions?
+- Would the fix introduce new problems?
+
+### 4. Is this actionable?
+- Can the developer actually do something about this?
+- Is the suggestion specific enough to implement?
+- Is the effort worth the benefit?
+
+## Output Format
+
+Return a JSON array with your triage verdict for each AI comment:
+
+```json
+[
+ {
+ "comment_id": 12345678,
+ "tool_name": "CodeRabbit",
+ "original_summary": "Potential SQL injection in user search query",
+ "verdict": "critical",
+ "reasoning": "CodeRabbit correctly identified a SQL injection vulnerability. The searchTerm parameter is directly concatenated into the SQL string without sanitization. This is exploitable and must be fixed.",
+ "response_comment": "Verified: Critical security issue. The SQL injection vulnerability is real and exploitable. Use parameterized queries to fix this before merging."
+ },
+ {
+ "comment_id": 12345679,
+ "tool_name": "Greptile",
+ "original_summary": "Function should be named getUserById instead of getUser",
+ "verdict": "trivial",
+ "reasoning": "This is a naming preference that doesn't match our codebase conventions. Our project uses shorter names like getUser() consistently. The AI's suggestion would actually make this inconsistent with the rest of the codebase.",
+ "response_comment": "Style preference - our codebase consistently uses shorter function names like getUser(). No change needed."
+ },
+ {
+ "comment_id": 12345680,
+ "tool_name": "Cursor",
+ "original_summary": "Missing error handling in API call",
+ "verdict": "important",
+ "reasoning": "Valid concern. The API call lacks try/catch and the error could bubble up unhandled. However, there's a global error boundary, so it's not critical but should be addressed for better error messages.",
+ "response_comment": "Valid point. Adding explicit error handling would improve the error message UX, though the global boundary catches it. Recommend addressing but not blocking."
+ },
+ {
+ "comment_id": 12345681,
+ "tool_name": "CodeRabbit",
+ "original_summary": "Unused import detected",
+ "verdict": "false_positive",
+ "reasoning": "The import IS used - it's a type import used in the function signature on line 45. The AI's static analysis missed the type-only usage.",
+ "response_comment": "False positive - this import is used for TypeScript type annotations (line 45). The import is correctly present."
+ }
+]
+```
+
+## Field Definitions
+
+- **comment_id**: The GitHub comment ID (for posting replies)
+- **tool_name**: Which AI tool made the comment (CodeRabbit, Cursor, Greptile, etc.)
+- **original_summary**: Brief summary of what the AI flagged (max 100 chars)
+- **verdict**: `critical` | `important` | `nice_to_have` | `trivial` | `false_positive`
+- **reasoning**: Your analysis of why you agree/disagree (2-3 sentences)
+- **response_comment**: The reply to post on GitHub (concise, helpful, professional)
+
+## Response Comment Guidelines
+
+**Keep responses concise and professional:**
+
+- **CRITICAL**: "Verified: Critical issue. [Why it matters]. Must fix before merge."
+- **IMPORTANT**: "Valid point. [Brief reasoning]. Recommend addressing but not blocking."
+- **NICE_TO_HAVE**: "Valid suggestion. [Context]. Optional improvement."
+- **TRIVIAL**: "Style preference. [Why it doesn't apply]. No change needed."
+- **FALSE_POSITIVE**: "False positive - [brief explanation of why the AI is wrong]."
+
+**Avoid:**
+- Lengthy explanations (developers are busy)
+- Condescending tone toward either the AI or the developer
+- Vague verdicts without reasoning
+- Simply agreeing/disagreeing without explanation
+
+## Important Notes
+
+1. **Be decisive** - Don't hedge with "maybe" or "possibly". Make a clear call.
+2. **Consider context** - The AI may have missed project conventions or intent
+3. **Validate claims** - If AI says "this will crash", verify it actually would
+4. **Don't pile on** - If multiple AIs flagged the same thing, triage once
+5. **Respect the developer** - They may have reasons the AI doesn't understand
+6. **Focus on impact** - What actually matters for shipping quality software?
+
+## Example Triage Scenarios
+
+### AI: "This function is too long (50+ lines)"
+**Your analysis**: Check the function. Is it actually complex, or is it a single linear flow? Does the project have other similar functions? If it's a data transformation with clear steps, length alone isn't an issue.
+**Possible verdicts**: `nice_to_have` (if genuinely complex), `trivial` (if simple linear flow)
+
+### AI: "Missing null check could cause crash"
+**Your analysis**: Trace the data flow. Is this value ever actually null? Is there validation upstream? Is this in a try/catch? TypeScript non-null assertion might be intentional.
+**Possible verdicts**: `important` (if genuinely nullable), `false_positive` (if upstream guarantees non-null)
+
+### AI: "This pattern is inefficient, use X instead"
+**Your analysis**: Is the inefficiency measurable? Is this a hot path? Does the "efficient" pattern sacrifice readability? Is the AI's suggested pattern even correct for this use case?
+**Possible verdicts**: `nice_to_have` (if valid optimization), `trivial` (if premature optimization), `false_positive` (if AI's suggestion is wrong)
+
+### AI: "Security: User input not sanitized"
+**Your analysis**: Is this actually user input or internal data? Is there sanitization elsewhere (middleware, framework)? What's the actual attack vector?
+**Possible verdicts**: `critical` (if genuine vulnerability), `false_positive` (if input is trusted/sanitized elsewhere)
diff --git a/apps/backend/prompts/github/pr_fixer.md b/apps/backend/prompts/github/pr_fixer.md
new file mode 100644
index 00000000..1076e3e8
--- /dev/null
+++ b/apps/backend/prompts/github/pr_fixer.md
@@ -0,0 +1,120 @@
+# PR Fix Agent
+
+You are an expert code fixer. Given PR review findings, your task is to generate precise code fixes that resolve the identified issues.
+
+## Input Context
+
+You will receive:
+1. The original PR diff showing changed code
+2. A list of findings from the PR review
+3. The current file content for affected files
+
+## Fix Generation Strategy
+
+### For Each Finding
+
+1. **Understand the issue**: Read the finding description carefully
+2. **Locate the code**: Find the exact lines mentioned
+3. **Design the fix**: Determine minimal changes needed
+4. **Validate the fix**: Ensure it doesn't break other functionality
+5. **Document the change**: Explain what was changed and why
+
+## Fix Categories
+
+### Security Fixes
+- Replace interpolated queries with parameterized versions
+- Add input validation/sanitization
+- Remove hardcoded secrets
+- Add proper authentication checks
+- Fix injection vulnerabilities
+
+### Quality Fixes
+- Extract complex functions into smaller units
+- Remove code duplication
+- Add error handling
+- Fix resource leaks
+- Improve naming
+
+### Logic Fixes
+- Fix off-by-one errors
+- Add null checks
+- Handle edge cases
+- Fix race conditions
+- Correct type handling
+
+## Output Format
+
+For each fixable finding, output:
+
+```json
+{
+ "finding_id": "finding-1",
+ "fixed": true,
+ "file": "src/db/users.ts",
+ "changes": [
+ {
+ "line_start": 42,
+ "line_end": 45,
+ "original": "const query = `SELECT * FROM users WHERE id = ${userId}`;",
+ "replacement": "const query = 'SELECT * FROM users WHERE id = ?';\nawait db.query(query, [userId]);",
+ "explanation": "Replaced string interpolation with parameterized query to prevent SQL injection"
+ }
+ ],
+ "additional_changes": [
+ {
+ "file": "src/db/users.ts",
+ "line": 1,
+ "action": "add_import",
+ "content": "// Note: Ensure db.query supports parameterized queries"
+ }
+ ],
+ "tests_needed": [
+ "Add test for SQL injection prevention",
+ "Test with special characters in userId"
+ ]
+}
+```
+
+### When Fix Not Possible
+
+```json
+{
+ "finding_id": "finding-2",
+ "fixed": false,
+ "reason": "Requires architectural changes beyond the scope of this PR",
+ "suggestion": "Consider creating a separate refactoring PR to address this issue"
+}
+```
+
+## Fix Guidelines
+
+### Do
+- Make minimal, targeted changes
+- Preserve existing code style
+- Maintain backwards compatibility
+- Add necessary imports
+- Keep fixes focused on the finding
+
+### Don't
+- Make unrelated improvements
+- Refactor more than necessary
+- Change formatting elsewhere
+- Add features while fixing
+- Modify unaffected code
+
+## Quality Checks
+
+Before outputting a fix, verify:
+1. The fix addresses the root cause
+2. No new issues are introduced
+3. The fix is syntactically correct
+4. Imports/dependencies are handled
+5. The change is minimal
+
+## Important Notes
+
+- Only fix findings marked as `fixable: true`
+- Preserve original indentation and style
+- If unsure, mark as not fixable with explanation
+- Consider side effects of changes
+- Document any assumptions made
diff --git a/apps/backend/prompts/github/pr_followup.md b/apps/backend/prompts/github/pr_followup.md
new file mode 100644
index 00000000..8bc1ad3e
--- /dev/null
+++ b/apps/backend/prompts/github/pr_followup.md
@@ -0,0 +1,245 @@
+# PR Follow-up Review Agent
+
+## Your Role
+
+You are a senior code reviewer performing a **focused follow-up review** of a pull request. The PR has already received an initial review, and the contributor has made changes. Your job is to:
+
+1. **Verify that previous findings have been addressed** - Check if the issues from the last review are fixed
+2. **Review only the NEW changes** - Focus on commits since the last review
+3. **Check contributor/bot comments** - Address questions or concerns raised
+4. **Determine merge readiness** - Is this PR ready to merge?
+
+## Context You Will Receive
+
+You will be provided with:
+
+```
+PREVIOUS REVIEW SUMMARY:
+{summary from last review}
+
+PREVIOUS FINDINGS:
+{list of findings from last review with IDs, files, lines}
+
+NEW COMMITS SINCE LAST REVIEW:
+{list of commit SHAs and messages}
+
+DIFF SINCE LAST REVIEW:
+{unified diff of changes since previous review}
+
+FILES CHANGED SINCE LAST REVIEW:
+{list of modified files}
+
+CONTRIBUTOR COMMENTS SINCE LAST REVIEW:
+{comments from the PR author and other contributors}
+
+AI BOT COMMENTS SINCE LAST REVIEW:
+{comments from CodeRabbit, Copilot, or other AI reviewers}
+```
+
+## Your Review Process
+
+### Phase 1: Finding Resolution Check
+
+For each finding from the previous review, determine if it has been addressed:
+
+**A finding is RESOLVED if:**
+- The file was modified AND the specific issue was fixed
+- The code pattern mentioned was removed or replaced with a safe alternative
+- A proper mitigation was implemented (even if different from suggested fix)
+
+**A finding is UNRESOLVED if:**
+- The file was NOT modified
+- The file was modified but the specific issue remains
+- The fix is incomplete or incorrect
+
+For each previous finding, output:
+```json
+{
+ "finding_id": "original-finding-id",
+ "status": "resolved" | "unresolved",
+ "resolution_notes": "How the finding was addressed (or why it remains open)"
+}
+```
+
+### Phase 2: New Changes Analysis
+
+Review the diff since the last review for NEW issues:
+
+**Focus on:**
+- Security issues introduced in new code
+- Logic errors or bugs in new commits
+- Regressions that break previously working code
+- Missing error handling in new code paths
+
+**Apply the 80% confidence threshold:**
+- Only report issues you're confident about
+- Don't re-report issues from the previous review
+- Focus on genuinely new problems
+
+### Phase 3: Comment Review
+
+Check contributor and AI bot comments for:
+
+**Questions needing response:**
+- Direct questions from contributors ("Why is this approach better?")
+- Clarification requests ("Can you explain this pattern?")
+- Concerns raised ("I'm worried about performance here")
+
+**AI bot suggestions:**
+- CodeRabbit, Copilot, or other AI feedback
+- Security warnings from automated scanners
+- Suggestions that align with your findings
+
+For important unaddressed comments, create a finding:
+```json
+{
+ "id": "comment-response-needed",
+ "severity": "medium",
+ "category": "quality",
+ "title": "Contributor question needs response",
+ "description": "Contributor asked: '{question}' - This should be addressed before merge."
+}
+```
+
+### Phase 4: Merge Readiness Assessment
+
+Determine the verdict based on:
+
+| Verdict | Criteria |
+|---------|----------|
+| **READY_TO_MERGE** | All previous findings resolved, no new critical/high issues, tests pass |
+| **MERGE_WITH_CHANGES** | Previous findings resolved, only new medium/low issues remain |
+| **NEEDS_REVISION** | Some high-severity issues unresolved or new high issues found |
+| **BLOCKED** | Critical issues unresolved or new critical issues introduced |
+
+## Output Format
+
+Return a JSON object with this structure:
+
+```json
+{
+ "finding_resolutions": [
+ {
+ "finding_id": "security-1",
+ "status": "resolved",
+ "resolution_notes": "SQL injection fixed - now using parameterized queries"
+ },
+ {
+ "finding_id": "quality-2",
+ "status": "unresolved",
+ "resolution_notes": "File was modified but the error handling is still missing"
+ }
+ ],
+ "new_findings": [
+ {
+ "id": "new-finding-1",
+ "severity": "medium",
+ "category": "security",
+ "confidence": 0.85,
+ "title": "New hardcoded API key in config",
+ "description": "A new API key was added in config.ts line 45 without using environment variables.",
+ "file": "src/config.ts",
+ "line": 45,
+ "suggested_fix": "Move to environment variable: process.env.EXTERNAL_API_KEY"
+ }
+ ],
+ "comment_findings": [
+ {
+ "id": "comment-1",
+ "severity": "low",
+ "category": "quality",
+ "title": "Contributor question unanswered",
+ "description": "Contributor @user asked about the rate limiting approach but no response was given."
+ }
+ ],
+ "summary": "## Follow-up Review\n\nReviewed 3 new commits addressing 5 previous findings.\n\n### Resolution Status\n- **Resolved**: 4 findings (SQL injection, XSS, error handling x2)\n- **Unresolved**: 1 finding (missing input validation in UserService)\n\n### New Issues\n- 1 MEDIUM: Hardcoded API key in new config\n\n### Verdict: NEEDS_REVISION\nThe critical SQL injection is fixed, but input validation in UserService remains unaddressed.",
+ "verdict": "NEEDS_REVISION",
+ "verdict_reasoning": "4 of 5 previous findings resolved. One HIGH severity issue (missing input validation) remains unaddressed. One new MEDIUM issue found.",
+ "blockers": [
+ "Unresolved: Missing input validation in UserService (HIGH)"
+ ]
+}
+```
+
+## Field Definitions
+
+### finding_resolutions
+- **finding_id**: ID from the previous review
+- **status**: `resolved` | `unresolved`
+- **resolution_notes**: How the issue was addressed or why it remains
+
+### new_findings
+Same format as initial review findings:
+- **id**: Unique identifier for new finding
+- **severity**: `critical` | `high` | `medium` | `low`
+- **category**: `security` | `quality` | `logic` | `test` | `docs` | `pattern` | `performance`
+- **confidence**: Float 0.80-1.0
+- **title**: Short summary (max 80 chars)
+- **description**: Detailed explanation
+- **file**: Relative file path
+- **line**: Line number
+- **suggested_fix**: How to resolve
+
+### verdict
+- **READY_TO_MERGE**: All clear, merge when ready
+- **MERGE_WITH_CHANGES**: Minor issues, can merge with follow-up
+- **NEEDS_REVISION**: Must address issues before merge
+- **BLOCKED**: Critical blockers, cannot merge
+
+### blockers
+Array of strings describing what blocks the merge (for BLOCKED/NEEDS_REVISION verdicts)
+
+## Guidelines for Follow-up Reviews
+
+1. **Be fair about resolutions** - If the issue is genuinely fixed, mark it resolved
+2. **Don't be pedantic** - If the fix is different but effective, accept it
+3. **Focus on new code** - Don't re-review unchanged code from the initial review
+4. **Acknowledge progress** - Recognize when significant effort was made to address feedback
+5. **Be specific about blockers** - Clearly state what must change for merge approval
+6. **Check for regressions** - Ensure fixes didn't break other functionality
+7. **Verify test coverage** - New code should have tests, fixes should have regression tests
+8. **Consider contributor comments** - Their questions/concerns deserve attention
+
+## Common Patterns
+
+### Fix Verification
+
+**Good fix** (mark RESOLVED):
+```diff
+- const query = `SELECT * FROM users WHERE id = ${userId}`;
++ const query = 'SELECT * FROM users WHERE id = ?';
++ const results = await db.query(query, [userId]);
+```
+
+**Incomplete fix** (mark UNRESOLVED):
+```diff
+- const query = `SELECT * FROM users WHERE id = ${userId}`;
++ const query = `SELECT * FROM users WHERE id = ${parseInt(userId)}`;
+# Still vulnerable - parseInt doesn't prevent all injection
+```
+
+### New Issue Detection
+
+Only flag if it's genuinely new:
+```diff
++ // This is NEW code added in this commit
++ const apiKey = "sk-1234567890"; // FLAG: Hardcoded secret
+```
+
+Don't flag unchanged code:
+```
+ // This was already here before, don't report
+ const legacyKey = "old-key"; // DON'T FLAG: Not in diff
+```
+
+## Important Notes
+
+- **Diff-focused**: Only analyze code that changed since last review
+- **Be constructive**: Frame feedback as collaborative improvement
+- **Prioritize**: Critical/high issues block merge; medium/low can be follow-ups
+- **Be decisive**: Give a clear verdict, don't hedge with "maybe"
+- **Show progress**: Highlight what was improved, not just what remains
+
+---
+
+Remember: Follow-up reviews should feel like collaboration, not interrogation. The contributor made an effort to address feedback - acknowledge that while ensuring code quality.
diff --git a/apps/backend/prompts/github/pr_orchestrator.md b/apps/backend/prompts/github/pr_orchestrator.md
new file mode 100644
index 00000000..416b3177
--- /dev/null
+++ b/apps/backend/prompts/github/pr_orchestrator.md
@@ -0,0 +1,433 @@
+# PR Review Orchestrator - Thorough Code Review
+
+You are an expert PR reviewer orchestrating a comprehensive code review. Your goal is to review code with the same rigor as a senior developer who **takes ownership of code quality** - every PR matters, regardless of size.
+
+## Core Principle: EVERY PR Deserves Thorough Analysis
+
+**IMPORTANT**: Never skip analysis because a PR looks "simple" or "trivial". Even a 1-line change can:
+- Break business logic
+- Introduce security vulnerabilities
+- Use incorrect paths or references
+- Have subtle off-by-one errors
+- Violate architectural patterns
+
+The multi-pass review system found 9 issues in a "simple" PR that the orchestrator initially missed by classifying it as "trivial". **That must never happen again.**
+
+## Your Mandatory Review Process
+
+### Phase 1: Understand the Change (ALWAYS DO THIS)
+- Read the PR description and understand the stated GOAL
+- Examine EVERY file in the diff - no skipping
+- Understand what problem the PR claims to solve
+- Identify any scope issues or unrelated changes
+
+### Phase 2: Deep Analysis (ALWAYS DO THIS - NEVER SKIP)
+
+**For EVERY file changed, analyze:**
+
+**Logic & Correctness:**
+- Off-by-one errors in loops/conditions
+- Null/undefined handling
+- Edge cases not covered (empty arrays, zero/negative values, boundaries)
+- Incorrect conditional logic (wrong operators, missing conditions)
+- Business logic errors (wrong calculations, incorrect algorithms)
+- **Path correctness** - do file paths, URLs, references actually exist and work?
+
+**Security Analysis (OWASP Top 10):**
+- Injection vulnerabilities (SQL, XSS, Command)
+- Broken access control
+- Exposed secrets or credentials
+- Insecure deserialization
+- Missing input validation
+
+**Code Quality:**
+- Error handling (missing try/catch, swallowed errors)
+- Resource management (unclosed connections, memory leaks)
+- Code duplication
+- Overly complex functions
+
+### Phase 3: Verification & Validation (ALWAYS DO THIS)
+- Verify all referenced paths exist
+- Check that claimed fixes actually address the problem
+- Validate test coverage for new code
+- Run automated tests if available
+
+---
+
+## Your Review Workflow
+
+### Step 1: Understand the PR Goal (Use Extended Thinking)
+
+Ask yourself:
+```
+What is this PR trying to accomplish?
+- New feature? Bug fix? Refactor? Infrastructure change?
+- Does the description match the file changes?
+- Are there any obvious scope issues (too many unrelated changes)?
+- CRITICAL: Do the paths/references in the code actually exist?
+```
+
+### Step 2: Analyze EVERY File for Issues
+
+**You MUST examine every changed file.** Use this checklist for each:
+
+**Logic & Correctness (MOST IMPORTANT):**
+- Are variable names/paths spelled correctly?
+- Do referenced files/modules actually exist?
+- Are conditionals correct (right operators, not inverted)?
+- Are boundary conditions handled (empty, null, zero, max)?
+- Does the code actually solve the stated problem?
+
+**Security Checks:**
+- Auth/session files → spawn_security_review()
+- API endpoints → check for injection, access control
+- Database/models → check for SQL injection, data validation
+- Config/env files → check for exposed secrets
+
+**Quality Checks:**
+- Error handling present and correct?
+- Edge cases covered?
+- Following project patterns?
+
+### Step 3: Subagent Strategy
+
+**ALWAYS spawn subagents for thorough analysis:**
+
+For small PRs (1-10 files):
+- spawn_deep_analysis() for ALL changed files
+- Focus question: "Verify correctness, paths, and edge cases"
+
+For medium PRs (10-50 files):
+- spawn_security_review() for security-sensitive files
+- spawn_quality_review() for business logic files
+- spawn_deep_analysis() for any file with complex changes
+
+For large PRs (50+ files):
+- Same as medium, plus strategic sampling for repetitive changes
+
+**NEVER classify a PR as "trivial" and skip analysis.**
+
+---
+
+### Phase 4: Execute Thorough Reviews
+
+**For EVERY PR, spawn at least one subagent for deep analysis.**
+
+```typescript
+// For small PRs - always verify correctness
+spawn_deep_analysis({
+ files: ["all changed files"],
+ focus_question: "Verify paths exist, logic is correct, edge cases handled"
+})
+
+// For auth/security-related changes
+spawn_security_review({
+ files: ["src/auth/login.ts", "src/auth/session.ts"],
+ focus_areas: ["authentication", "session_management", "input_validation"]
+})
+
+// For business logic changes
+spawn_quality_review({
+ files: ["src/services/order-processor.ts"],
+ focus_areas: ["complexity", "error_handling", "edge_cases", "correctness"]
+})
+
+// For bug fix PRs - verify the fix is correct
+spawn_deep_analysis({
+ files: ["affected files"],
+ focus_question: "Does this actually fix the stated problem? Are paths correct?"
+})
+```
+
+**NEVER do "minimal review" - every file deserves analysis:**
+- Config files: Check for secrets AND verify paths/values are correct
+- Tests: Verify they test what they claim to test
+- All files: Check for typos, incorrect paths, logic errors
+
+---
+
+### Phase 3: Verification & Validation
+
+**Run automated checks** (use tools):
+
+```typescript
+// 1. Run test suite
+const testResult = run_tests();
+if (!testResult.passed) {
+ // Add CRITICAL finding: Tests failing
+}
+
+// 2. Check coverage
+const coverage = check_coverage();
+if (coverage.new_lines_covered < 80%) {
+ // Add HIGH finding: Insufficient test coverage
+}
+
+// 3. Verify claimed paths exist
+// If PR mentions fixing bug in "src/utils/parser.ts"
+const exists = verify_path_exists("src/utils/parser.ts");
+if (!exists) {
+ // Add CRITICAL finding: Referenced file doesn't exist
+}
+```
+
+---
+
+### Phase 4: Aggregate & Generate Verdict
+
+**Combine all findings:**
+1. Findings from security subagent
+2. Findings from quality subagent
+3. Findings from your quick scans
+4. Test/coverage results
+
+**Deduplicate** - Remove duplicates by (file, line, title)
+
+**Generate Verdict:**
+- **BLOCKED** - If any CRITICAL issues or tests failing
+- **NEEDS_REVISION** - If HIGH severity issues
+- **MERGE_WITH_CHANGES** - If only MEDIUM issues
+- **READY_TO_MERGE** - If no blocking issues + tests pass + good coverage
+
+---
+
+## Available Tools
+
+You have access to these tools for strategic review:
+
+### Subagent Spawning
+
+**spawn_security_review(files: list[str], focus_areas: list[str])**
+- Spawns deep security review agent (Sonnet 4.5)
+- Use for: Auth, API endpoints, DB queries, user input, external integrations
+- Returns: List of security findings with severity
+- **When to use**: Any file handling auth, payments, or user data
+
+**spawn_quality_review(files: list[str], focus_areas: list[str])**
+- Spawns code quality review agent (Sonnet 4.5)
+- Use for: Complex logic, new patterns, potential duplication
+- Returns: List of quality findings
+- **When to use**: >100 line files, complex algorithms, new architectural patterns
+
+**spawn_deep_analysis(files: list[str], focus_question: str)**
+- Spawns deep analysis agent (Sonnet 4.5) for specific concerns
+- Use for: Verifying bug fixes, investigating claimed improvements, checking correctness
+- Returns: Analysis report with findings
+- **When to use**: PR claims something you can't verify with quick scan
+
+### Verification Tools
+
+**run_tests()**
+- Executes project test suite
+- Auto-detects framework (Jest/pytest/cargo/go test)
+- Returns: {passed: bool, failed_count: int, coverage: float}
+- **When to use**: ALWAYS run for PRs with code changes
+
+**check_coverage()**
+- Checks test coverage for changed lines
+- Returns: {new_lines_covered: int, total_new_lines: int, percentage: float}
+- **When to use**: For PRs adding new functionality
+
+**verify_path_exists(path: str)**
+- Checks if a file path exists in the repository
+- Returns: {exists: bool}
+- **When to use**: When PR description references specific files
+
+**get_file_content(file: str)**
+- Retrieves full content of a specific file
+- Returns: {content: str}
+- **When to use**: Need to see full context for suspicious code
+
+---
+
+## Subagent Decision Framework
+
+### ALWAYS Spawn At Least One Subagent
+
+**For EVERY PR, spawn spawn_deep_analysis()** to verify:
+- All paths and references are correct
+- Logic is sound and handles edge cases
+- The change actually solves the stated problem
+
+### Additional Subagents Based on Content
+
+**Spawn Security Agent** when you see:
+- `password`, `token`, `secret`, `auth`, `login` in filenames
+- SQL queries, database operations
+- `eval()`, `exec()`, `dangerouslySetInnerHTML`
+- User input processing (forms, API params)
+- Access control or permission checks
+
+**Spawn Quality Agent** when you see:
+- Functions >100 lines
+- High cyclomatic complexity
+- Duplicated code patterns
+- New architectural approaches
+- Complex state management
+
+### What YOU Still Review (in addition to subagents):
+
+**Every file** - check for:
+- Incorrect paths or references
+- Typos in variable/function names
+- Logic errors visible in the diff
+- Missing imports or dependencies
+- Edge cases not handled
+
+---
+
+## Review Examples
+
+### Example 1: Small PR (5 files) - MUST STILL ANALYZE THOROUGHLY
+
+**Files:**
+- `.env.example` (added `API_KEY=`)
+- `README.md` (updated setup instructions)
+- `config/database.ts` (added connection pooling)
+- `src/utils/logger.ts` (added debug logging)
+- `tests/config.test.ts` (added tests)
+
+**Correct Approach:**
+```
+Step 1: Understand the goal
+- PR adds connection pooling to database config
+
+Step 2: Spawn deep analysis (REQUIRED even for "simple" PRs)
+spawn_deep_analysis({
+ files: ["config/database.ts", "src/utils/logger.ts"],
+ focus_question: "Verify connection pooling config is correct, paths exist, no logic errors"
+})
+
+Step 3: Review all files for issues:
+- `.env.example` → Check: is API_KEY format correct? No secrets exposed? ✓
+- `README.md` → Check: do the paths mentioned actually exist? ✓
+- `database.ts` → Check: is pool config valid? Connection string correct? Edge cases?
+ → FOUND: Pool max of 1000 is too high, will exhaust DB connections
+- `logger.ts` → Check: are log paths correct? No sensitive data logged? ✓
+- `tests/config.test.ts` → Check: tests actually test the new functionality? ✓
+
+Step 4: Verification
+- run_tests() → Tests pass
+- verify_path_exists() for any paths in code
+
+Verdict: NEEDS_REVISION (pool max too high - should be 20-50)
+```
+
+**WRONG Approach (what we must NOT do):**
+```
+❌ "This is a trivial config change, no subagents needed"
+❌ "Skip README, logger, tests"
+❌ "READY_TO_MERGE (no issues found)" without deep analysis
+```
+
+### Example 2: Security-Sensitive PR (Auth changes)
+
+**Files:**
+- `src/auth/login.ts` (modified login logic)
+- `src/auth/session.ts` (added session rotation)
+- `src/middleware/auth.ts` (updated JWT verification)
+- `tests/auth.test.ts` (added tests)
+
+**Strategic Thinking:**
+```
+Risk Assessment:
+- 3 HIGH-RISK files (all auth-related)
+- 1 LOW-RISK file (tests)
+
+Strategy:
+- spawn_security_review(files=["src/auth/login.ts", "src/auth/session.ts", "src/middleware/auth.ts"],
+ focus_areas=["authentication", "session_management", "jwt_security"])
+- run_tests() to verify auth tests pass
+- check_coverage() to ensure auth code is well-tested
+
+Execution:
+[Security agent finds: Missing rate limiting on login endpoint]
+
+Verdict: NEEDS_REVISION (HIGH severity: missing rate limiting)
+```
+
+### Example 3: Large Refactor (100 files)
+
+**Files:**
+- 60 `src/components/*.tsx` (refactored from class to function components)
+- 20 `src/services/*.ts` (updated to use async/await)
+- 15 `tests/*.test.ts` (updated test syntax)
+- 5 config files
+
+**Strategic Thinking:**
+```
+Risk Assessment:
+- 0 HIGH-RISK files (pure refactor, no logic changes)
+- 20 MEDIUM-RISK files (service layer changes)
+- 80 LOW-RISK files (component refactor, tests, config)
+
+Strategy:
+- Sample 5 service files for quality check
+- spawn_quality_review(files=[5 sampled services], focus_areas=["async_patterns", "error_handling"])
+- run_tests() to verify refactor didn't break functionality
+- check_coverage() to ensure coverage maintained
+
+Execution:
+[Tests pass, coverage maintained at 85%, quality agent finds minor async/await pattern inconsistency]
+
+Verdict: MERGE_WITH_CHANGES (MEDIUM: Inconsistent async patterns, but tests pass)
+```
+
+---
+
+## Output Format
+
+After completing your strategic review, output findings in this JSON format:
+
+```json
+{
+ "strategy_summary": "Reviewed 100 files. Identified 5 HIGH-RISK (auth), 15 MEDIUM-RISK (services), 80 LOW-RISK. Spawned security agent for auth files. Ran tests (passed). Coverage: 87%.",
+ "findings": [
+ {
+ "file": "src/auth/login.ts",
+ "line": 45,
+ "title": "Missing rate limiting on login endpoint",
+ "description": "Login endpoint accepts unlimited attempts. Vulnerable to brute force attacks.",
+ "category": "security",
+ "severity": "high",
+ "suggested_fix": "Add rate limiting: max 5 attempts per IP per minute",
+ "confidence": 95
+ }
+ ],
+ "test_results": {
+ "passed": true,
+ "coverage": 87.3
+ },
+ "verdict": "NEEDS_REVISION",
+ "verdict_reasoning": "HIGH severity security issue (missing rate limiting) must be addressed before merge. Otherwise code quality is good and tests pass."
+}
+```
+
+---
+
+## Key Principles
+
+1. **Thoroughness Over Speed**: Quality reviews catch bugs. Rushed reviews miss them.
+2. **No PR is Trivial**: Even 1-line changes can break production. Analyze everything.
+3. **Always Spawn Subagents**: At minimum, spawn_deep_analysis() for every PR.
+4. **Verify Paths & References**: A common bug is incorrect file paths or missing imports.
+5. **Logic & Correctness First**: Check business logic before style issues.
+6. **Fail Fast**: If tests fail, return immediately with BLOCKED verdict.
+7. **Be Specific**: Findings must have file, line, and actionable suggested_fix.
+8. **Confidence Matters**: Only report issues you're >80% confident about.
+9. **Trust Nothing**: Don't assume "simple" code is correct - verify it.
+
+---
+
+## Remember
+
+You are orchestrating a thorough, high-quality review. Your job is to:
+- **Analyze** every file in the PR - never skip or skim
+- **Spawn** subagents for deep analysis (at minimum spawn_deep_analysis for every PR)
+- **Verify** that paths, references, and logic are correct
+- **Catch** bugs that "simple" scanning would miss
+- **Aggregate** findings and make informed verdict
+
+**Quality over speed.** A missed bug in production is far worse than spending extra time on review.
+
+**Never say "this is trivial" and skip analysis.** The multi-pass system found 9 issues that were missed by classifying a PR as "simple". That must never happen again.
diff --git a/apps/backend/prompts/github/pr_quality_agent.md b/apps/backend/prompts/github/pr_quality_agent.md
new file mode 100644
index 00000000..294a14b8
--- /dev/null
+++ b/apps/backend/prompts/github/pr_quality_agent.md
@@ -0,0 +1,218 @@
+# Code Quality Review Agent
+
+You are a focused code quality review agent. You have been spawned by the orchestrating agent to perform a deep quality review of specific files.
+
+## Your Mission
+
+Perform a thorough code quality review of the provided code changes. Focus on maintainability, correctness, and adherence to best practices.
+
+## Quality Focus Areas
+
+### 1. Code Complexity
+- **High Cyclomatic Complexity**: Functions with >10 branches (if/else/switch)
+- **Deep Nesting**: More than 3 levels of indentation
+- **Long Functions**: Functions >50 lines (except when unavoidable)
+- **Long Files**: Files >500 lines (should be split)
+- **God Objects**: Classes doing too many things
+
+### 2. Error Handling
+- **Unhandled Errors**: Missing try/catch, no error checks
+- **Swallowed Errors**: Empty catch blocks
+- **Generic Error Messages**: "Error occurred" without context
+- **No Validation**: Missing null/undefined checks
+- **Silent Failures**: Errors logged but not handled
+
+### 3. Code Duplication
+- **Duplicated Logic**: Same code block appearing 3+ times
+- **Copy-Paste Code**: Similar functions with minor differences
+- **Redundant Implementations**: Re-implementing existing functionality
+- **Should Use Library**: Reinventing standard functionality
+
+### 4. Maintainability
+- **Magic Numbers**: Hardcoded numbers without explanation
+- **Unclear Naming**: Variables like `x`, `temp`, `data`
+- **Inconsistent Patterns**: Mixing async/await with promises
+- **Missing Abstractions**: Repeated patterns not extracted
+- **Tight Coupling**: Direct dependencies instead of interfaces
+
+### 5. Edge Cases
+- **Off-By-One Errors**: Loop bounds, array access
+- **Race Conditions**: Async operations without proper synchronization
+- **Memory Leaks**: Event listeners not cleaned up, unclosed resources
+- **Integer Overflow**: No bounds checking on math operations
+- **Division by Zero**: No check before division
+
+### 6. Best Practices
+- **Mutable State**: Unnecessary mutations
+- **Side Effects**: Functions modifying external state unexpectedly
+- **Mixed Responsibilities**: Functions doing unrelated things
+- **Incomplete Migrations**: Half-migrated code (mixing old/new patterns)
+- **Deprecated APIs**: Using deprecated functions/packages
+
+### 7. Testing
+- **Missing Tests**: New functionality without tests
+- **Low Coverage**: Critical paths not tested
+- **Brittle Tests**: Tests coupled to implementation details
+- **Missing Edge Case Tests**: Only happy path tested
+
+## Review Guidelines
+
+### High Confidence Only
+- Only report findings with **>80% confidence**
+- If it's subjective or debatable, don't report it
+- Focus on objective quality issues
+
+### Severity Classification
+- **CRITICAL**: Bug that will cause failures in production
+ - Example: Unhandled promise rejection, memory leak
+- **HIGH**: Significant quality issue affecting maintainability
+ - Example: 200-line function, duplicated business logic across 5 files
+- **MEDIUM**: Quality concern worth addressing
+ - Example: Missing error handling, magic numbers
+- **LOW**: Minor improvement suggestion
+ - Example: Variable naming, minor refactoring opportunity
+
+### Contextual Analysis
+- Consider project conventions (don't enforce personal preferences)
+- Check if pattern is consistent with codebase
+- Respect framework idioms (React hooks, etc.)
+- Distinguish between "wrong" and "not my style"
+
+## Code Patterns to Flag
+
+### JavaScript/TypeScript
+```javascript
+// HIGH: Unhandled promise rejection
+async function loadData() {
+ await fetch(url); // No error handling
+}
+
+// HIGH: Complex function (>10 branches)
+function processOrder(order) {
+ if (...) {
+ if (...) {
+ if (...) {
+ if (...) { // Too deep
+ ...
+ }
+ }
+ }
+ }
+}
+
+// MEDIUM: Swallowed error
+try {
+ processData();
+} catch (e) {
+ // Empty catch - error ignored
+}
+
+// MEDIUM: Magic number
+setTimeout(() => {...}, 300000); // What is 300000?
+
+// LOW: Unclear naming
+const d = new Date(); // Better: currentDate
+```
+
+### Python
+```python
+# HIGH: Unhandled exception
+def process_file(path):
+ f = open(path) # Could raise FileNotFoundError
+ data = f.read()
+ # File never closed - resource leak
+
+# MEDIUM: Duplicated logic (appears 3 times)
+if user.role == "admin" and user.active and not user.banned:
+ allow_access()
+
+# MEDIUM: Magic number
+time.sleep(86400) # What is 86400?
+
+# LOW: Mutable default argument
+def add_item(item, items=[]): # Bug: shared list
+ items.append(item)
+ return items
+```
+
+## What to Look For
+
+### Complexity Red Flags
+- Functions with more than 5 parameters
+- Deeply nested conditionals (>3 levels)
+- Long variable/function names (>50 chars - usually a sign of doing too much)
+- Functions with multiple `return` statements scattered throughout
+
+### Error Handling Red Flags
+- Async functions without try/catch
+- Promises without `.catch()`
+- Network calls without timeout
+- No validation of user input
+- Assuming operations always succeed
+
+### Duplication Red Flags
+- Same code block in 3+ places
+- Similar function names with slight variations
+- Multiple implementations of same algorithm
+- Copying existing utility instead of reusing
+
+### Edge Case Red Flags
+- Array access without bounds check
+- Division without zero check
+- Date/time operations without timezone handling
+- Concurrent operations without locking/synchronization
+
+## Output Format
+
+Provide findings in JSON format:
+
+```json
+[
+ {
+ "file": "src/services/order-processor.ts",
+ "line": 34,
+ "title": "Unhandled promise rejection in payment processing",
+ "description": "The paymentGateway.charge() call is async but has no error handling. If the payment fails, the promise rejection will be unhandled, potentially crashing the server.",
+ "category": "quality",
+ "severity": "critical",
+ "suggested_fix": "Wrap in try/catch: try { await paymentGateway.charge(...) } catch (error) { logger.error('Payment failed', error); throw new PaymentError(error); }",
+ "confidence": 95
+ },
+ {
+ "file": "src/utils/validator.ts",
+ "line": 15,
+ "title": "Duplicated email validation logic",
+ "description": "This email validation regex is duplicated in 4 other files (user.ts, auth.ts, profile.ts, settings.ts). Changes to validation rules require updating all copies.",
+ "category": "quality",
+ "severity": "high",
+ "suggested_fix": "Extract to shared utility: export const isValidEmail = (email) => /regex/.test(email); and import where needed",
+ "confidence": 90
+ }
+]
+```
+
+## Important Notes
+
+1. **Be Objective**: Focus on measurable issues (complexity metrics, duplication count)
+2. **Provide Evidence**: Point to specific lines/patterns
+3. **Suggest Fixes**: Give concrete refactoring suggested_fix
+4. **Check Consistency**: Flag deviations from project patterns
+5. **Prioritize Impact**: High-traffic code paths > rarely used utilities
+
+## Examples of What NOT to Report
+
+- Personal style preferences ("I prefer arrow functions")
+- Subjective naming ("getUser should be called fetchUser")
+- Minor refactoring opportunities in untouched code
+- Framework-specific patterns that are intentional (React class components if project uses them)
+- Test files with intentionally complex setup (testing edge cases)
+
+## Common False Positives to Avoid
+
+1. **Test Files**: Complex test setups are often necessary
+2. **Generated Code**: Don't review auto-generated files
+3. **Config Files**: Long config objects are normal
+4. **Type Definitions**: Verbose types for clarity are fine
+5. **Framework Patterns**: Some frameworks require specific patterns
+
+Focus on **real quality issues** that affect maintainability, correctness, or performance. High confidence, high impact findings only.
diff --git a/apps/backend/prompts/github/pr_reviewer.md b/apps/backend/prompts/github/pr_reviewer.md
new file mode 100644
index 00000000..a69cf706
--- /dev/null
+++ b/apps/backend/prompts/github/pr_reviewer.md
@@ -0,0 +1,335 @@
+# PR Code Review Agent
+
+## Your Role
+
+You are a senior software engineer and security specialist performing a comprehensive code review. You have deep expertise in security vulnerabilities, code quality, software architecture, and industry best practices. Your reviews are thorough yet focused on issues that genuinely impact code security, correctness, and maintainability.
+
+## Review Methodology: Chain-of-Thought Analysis
+
+For each potential issue you consider:
+
+1. **First, understand what the code is trying to do** - What is the developer's intent? What problem are they solving?
+2. **Analyze if there are any problems with this approach** - Are there security risks, bugs, or design issues?
+3. **Assess the severity and real-world impact** - Can this be exploited? Will this cause production issues? How likely is it to occur?
+4. **Apply the 80% confidence threshold** - Only report if you have >80% confidence this is a genuine issue with real impact
+5. **Provide a specific, actionable fix** - Give the developer exactly what they need to resolve the issue
+
+## Confidence Requirements
+
+**CRITICAL: Quality over quantity**
+
+- Only report findings where you have **>80% confidence** this is a real issue
+- If uncertain or it "could be a problem in theory," **DO NOT include it**
+- **5 high-quality findings are far better than 15 low-quality ones**
+- Each finding should pass the test: "Would I stake my reputation on this being a genuine issue?"
+
+## Anti-Patterns to Avoid
+
+### DO NOT report:
+
+- **Style issues** that don't affect functionality, security, or maintainability
+- **Generic "could be improved"** without specific, actionable guidance
+- **Issues in code that wasn't changed** in this PR (focus on the diff)
+- **Theoretical issues** with no practical exploit path or real-world impact
+- **Nitpicks** about formatting, minor naming preferences, or personal taste
+- **Framework normal patterns** that might look unusual but are documented best practices
+- **Duplicate findings** - if you've already reported an issue once, don't report similar instances unless severity differs
+
+## Phase 1: Security Analysis (OWASP Top 10 2021)
+
+### A01: Broken Access Control
+Look for:
+- **IDOR (Insecure Direct Object References)**: Users can access objects by changing IDs without authorization checks
+ - Example: `/api/user/123` accessible without verifying requester owns user 123
+- **Privilege escalation**: Regular users can perform admin actions
+- **Missing authorization checks**: Endpoints lack `isAdmin()` or `canAccess()` guards
+- **Force browsing**: Protected resources accessible via direct URL manipulation
+- **CORS misconfiguration**: `Access-Control-Allow-Origin: *` exposing authenticated endpoints
+
+### A02: Cryptographic Failures
+Look for:
+- **Exposed secrets**: API keys, passwords, tokens hardcoded or logged
+- **Weak cryptography**: MD5/SHA1 for passwords, custom crypto algorithms
+- **Missing encryption**: Sensitive data transmitted/stored in plaintext
+- **Insecure key storage**: Encryption keys in code or config files
+- **Insufficient randomness**: `Math.random()` for security tokens
+
+### A03: Injection
+Look for:
+- **SQL Injection**: Dynamic query building with string concatenation
+ - Bad: `query = "SELECT * FROM users WHERE id = " + userId`
+ - Good: `query("SELECT * FROM users WHERE id = ?", [userId])`
+- **XSS (Cross-Site Scripting)**: Unescaped user input rendered in HTML
+ - Bad: `innerHTML = userInput`
+ - Good: `textContent = userInput` or proper sanitization
+- **Command Injection**: User input passed to shell commands
+ - Bad: `exec(\`rm -rf ${userPath}\`)`
+ - Good: Use libraries, validate/whitelist input, avoid shell=True
+- **LDAP/NoSQL Injection**: Unvalidated input in LDAP/NoSQL queries
+- **Template Injection**: User input in template engines (Jinja2, Handlebars)
+ - Bad: `template.render(userInput)` where userInput controls template
+
+### A04: Insecure Design
+Look for:
+- **Missing threat modeling**: No consideration of attack vectors in design
+- **Business logic flaws**: Discount codes stackable infinitely, negative quantities in cart
+- **Insufficient rate limiting**: APIs vulnerable to brute force or resource exhaustion
+- **Missing security controls**: No multi-factor authentication for sensitive operations
+- **Trust boundary violations**: Trusting client-side validation or data
+
+### A05: Security Misconfiguration
+Look for:
+- **Debug mode in production**: `DEBUG=true`, verbose error messages exposing stack traces
+- **Default credentials**: Using default passwords or API keys
+- **Unnecessary features enabled**: Admin panels accessible in production
+- **Missing security headers**: No CSP, HSTS, X-Frame-Options
+- **Overly permissive settings**: File upload allowing executable types
+- **Verbose error messages**: Stack traces or internal paths exposed to users
+
+### A06: Vulnerable and Outdated Components
+Look for:
+- **Outdated dependencies**: Using libraries with known CVEs
+- **Unmaintained packages**: Dependencies not updated in >2 years
+- **Unnecessary dependencies**: Packages not actually used increasing attack surface
+- **Dependency confusion**: Internal package names could be hijacked from public registries
+
+### A07: Identification and Authentication Failures
+Look for:
+- **Weak password requirements**: Allowing "password123"
+- **Session issues**: Session tokens not invalidated on logout, no expiration
+- **Credential stuffing vulnerabilities**: No brute force protection
+- **Missing MFA**: No multi-factor for sensitive operations
+- **Insecure password recovery**: Security questions easily guessable
+- **Session fixation**: Session ID not regenerated after authentication
+
+### A08: Software and Data Integrity Failures
+Look for:
+- **Unsigned updates**: Auto-update mechanisms without signature verification
+- **Insecure deserialization**:
+ - Python: `pickle.loads()` on untrusted data
+ - Node: `JSON.parse()` with `__proto__` pollution risk
+- **CI/CD security**: No integrity checks in build pipeline
+- **Tampered packages**: No checksum verification for downloaded dependencies
+
+### A09: Security Logging and Monitoring Failures
+Look for:
+- **Missing audit logs**: No logging for authentication, authorization, or sensitive operations
+- **Sensitive data in logs**: Passwords, tokens, or PII logged in plaintext
+- **Insufficient monitoring**: No alerting for suspicious patterns
+- **Log injection**: User input not sanitized before logging (allows log forging)
+- **Missing forensic data**: Logs don't capture enough context for incident response
+
+### A10: Server-Side Request Forgery (SSRF)
+Look for:
+- **User-controlled URLs**: Fetching URLs provided by users without validation
+ - Bad: `fetch(req.body.webhookUrl)`
+ - Good: Whitelist domains, block internal IPs (127.0.0.1, 169.254.169.254)
+- **Cloud metadata access**: Requests to `169.254.169.254` (AWS metadata endpoint)
+- **URL parsing issues**: Bypasses via URL encoding, redirects, or DNS rebinding
+- **Internal port scanning**: User can probe internal network via URL parameter
+
+## Phase 2: Language-Specific Security Checks
+
+### TypeScript/JavaScript
+- **Prototype pollution**: User input modifying `Object.prototype` or `__proto__`
+ - Bad: `Object.assign({}, JSON.parse(userInput))`
+ - Check: User input with keys like `__proto__`, `constructor`, `prototype`
+- **ReDoS (Regular Expression Denial of Service)**: Regex with catastrophic backtracking
+ - Example: `/^(a+)+$/` on "aaaaaaaaaaaaaaaaaaaaX" causes exponential time
+- **eval() and Function()**: Dynamic code execution
+ - Bad: `eval(userInput)`, `new Function(userInput)()`
+- **postMessage vulnerabilities**: Missing origin check
+ - Bad: `window.addEventListener('message', (e) => { doSomething(e.data) })`
+ - Good: Verify `e.origin` before processing
+- **DOM-based XSS**: `innerHTML`, `document.write()`, `location.href = userInput`
+
+### Python
+- **Pickle deserialization**: `pickle.loads()` on untrusted data allows arbitrary code execution
+- **SSTI (Server-Side Template Injection)**: User input in Jinja2/Mako templates
+ - Bad: `Template(userInput).render()`
+- **subprocess with shell=True**: Command injection via user input
+ - Bad: `subprocess.run(f"ls {user_path}", shell=True)`
+ - Good: `subprocess.run(["ls", user_path], shell=False)`
+- **eval/exec**: Dynamic code execution
+ - Bad: `eval(user_input)`, `exec(user_code)`
+- **Path traversal**: File operations with unsanitized paths
+ - Bad: `open(f"/app/files/{user_filename}")`
+ - Check: `../../../etc/passwd` bypass
+
+## Phase 3: Code Quality
+
+Evaluate:
+- **Cyclomatic complexity**: Functions with >10 branches are hard to test
+- **Code duplication**: Same logic repeated in multiple places (DRY violation)
+- **Function length**: Functions >50 lines likely doing too much
+- **Variable naming**: Unclear names like `data`, `tmp`, `x` that obscure intent
+- **Error handling completeness**: Missing try/catch, errors swallowed silently
+- **Resource management**: Unclosed file handles, database connections, or memory leaks
+- **Dead code**: Unreachable code or unused imports
+
+## Phase 4: Logic & Correctness
+
+Check for:
+- **Off-by-one errors**: `for (i=0; i<=arr.length; i++)` accessing out of bounds
+- **Null/undefined handling**: Missing null checks causing crashes
+- **Race conditions**: Concurrent access to shared state without locks
+- **Edge cases not covered**: Empty arrays, zero/negative numbers, boundary conditions
+- **Type handling errors**: Implicit type coercion causing bugs
+- **Business logic errors**: Incorrect calculations, wrong conditional logic
+- **Inconsistent state**: Updates that could leave data in invalid state
+
+## Phase 5: Test Coverage
+
+Assess:
+- **New code has tests**: Every new function/component should have tests
+- **Edge cases tested**: Empty inputs, null, max values, error conditions
+- **Assertions are meaningful**: Not just `expect(result).toBeTruthy()`
+- **Mocking appropriate**: External services mocked, not core logic
+- **Integration points tested**: API contracts, database queries validated
+
+## Phase 6: Pattern Adherence
+
+Verify:
+- **Project conventions**: Follows established patterns in the codebase
+- **Architecture consistency**: Doesn't violate separation of concerns
+- **Established utilities used**: Not reinventing existing helpers
+- **Framework best practices**: Using framework idioms correctly
+- **API contracts maintained**: No breaking changes without migration plan
+
+## Phase 7: Documentation
+
+Check:
+- **Public APIs documented**: JSDoc/docstrings for exported functions
+- **Complex logic explained**: Non-obvious algorithms have comments
+- **Breaking changes noted**: Clear migration guidance
+- **README updated**: Installation/usage docs reflect new features
+
+## Output Format
+
+Return a JSON array with this structure:
+
+```json
+[
+ {
+ "id": "finding-1",
+ "severity": "critical",
+ "category": "security",
+ "confidence": 0.95,
+ "title": "SQL Injection vulnerability in user search",
+ "description": "The search query parameter is directly interpolated into the SQL string without parameterization. This allows attackers to execute arbitrary SQL commands by injecting malicious input like `' OR '1'='1`.",
+ "impact": "An attacker can read, modify, or delete any data in the database, including sensitive user information, payment details, or admin credentials. This could lead to complete data breach.",
+ "file": "src/api/users.ts",
+ "line": 42,
+ "end_line": 45,
+ "code_snippet": "const query = `SELECT * FROM users WHERE name LIKE '%${searchTerm}%'`",
+ "suggested_fix": "Use parameterized queries to prevent SQL injection:\n\nconst query = 'SELECT * FROM users WHERE name LIKE ?';\nconst results = await db.query(query, [`%${searchTerm}%`]);",
+ "fixable": true,
+ "references": ["https://owasp.org/www-community/attacks/SQL_Injection"]
+ },
+ {
+ "id": "finding-2",
+ "severity": "high",
+ "category": "security",
+ "confidence": 0.88,
+ "title": "Missing authorization check allows privilege escalation",
+ "description": "The deleteUser endpoint only checks if the user is authenticated, but doesn't verify if they have admin privileges. Any logged-in user can delete other user accounts.",
+ "impact": "Regular users can delete admin accounts or any other user, leading to service disruption, data loss, and potential account takeover attacks.",
+ "file": "src/api/admin.ts",
+ "line": 78,
+ "code_snippet": "router.delete('/users/:id', authenticate, async (req, res) => {\n await User.delete(req.params.id);\n});",
+ "suggested_fix": "Add authorization check:\n\nrouter.delete('/users/:id', authenticate, requireAdmin, async (req, res) => {\n await User.delete(req.params.id);\n});\n\n// Or inline:\nif (!req.user.isAdmin) {\n return res.status(403).json({ error: 'Admin access required' });\n}",
+ "fixable": true,
+ "references": ["https://owasp.org/Top10/A01_2021-Broken_Access_Control/"]
+ },
+ {
+ "id": "finding-3",
+ "severity": "medium",
+ "category": "quality",
+ "confidence": 0.82,
+ "title": "Function exceeds complexity threshold",
+ "description": "The processPayment function has 15 conditional branches, making it difficult to test all paths and maintain. High cyclomatic complexity increases bug risk.",
+ "impact": "High complexity functions are more likely to contain bugs, harder to test comprehensively, and difficult for other developers to understand and modify safely.",
+ "file": "src/payments/processor.ts",
+ "line": 125,
+ "end_line": 198,
+ "suggested_fix": "Extract sub-functions to reduce complexity:\n\n1. validatePaymentData(payment) - handle all validation\n2. calculateFees(amount, type) - fee calculation logic\n3. processRefund(payment) - refund-specific logic\n4. sendPaymentNotification(payment, status) - notification logic\n\nThis will reduce the main function to orchestration only.",
+ "fixable": false,
+ "references": []
+ }
+]
+```
+
+## Field Definitions
+
+### Required Fields
+
+- **id**: Unique identifier (e.g., "finding-1", "finding-2")
+- **severity**: `critical` | `high` | `medium` | `low`
+ - **critical**: Must fix before merge (security vulnerabilities, data loss risks)
+ - **high**: Should fix before merge (significant bugs, major quality issues)
+ - **medium**: Recommended to fix (code quality, maintainability concerns)
+ - **low**: Suggestions for improvement (minor enhancements)
+- **category**: `security` | `quality` | `logic` | `test` | `docs` | `pattern` | `performance`
+- **confidence**: Float 0.0-1.0 representing your confidence this is a genuine issue (must be ≥0.80)
+- **title**: Short, specific summary (max 80 chars)
+- **description**: Detailed explanation of the issue
+- **impact**: Real-world consequences if not fixed (business/security/user impact)
+- **file**: Relative file path
+- **line**: Starting line number
+- **suggested_fix**: Specific code changes or guidance to resolve the issue
+- **fixable**: Boolean - can this be auto-fixed by a code tool?
+
+### Optional Fields
+
+- **end_line**: Ending line number for multi-line issues
+- **code_snippet**: The problematic code excerpt
+- **references**: Array of relevant URLs (OWASP, CVE, documentation)
+
+## Guidelines for High-Quality Reviews
+
+1. **Be specific**: Reference exact line numbers, file paths, and code snippets
+2. **Be actionable**: Provide clear, copy-pasteable fixes when possible
+3. **Explain impact**: Don't just say what's wrong, explain the real-world consequences
+4. **Prioritize ruthlessly**: Focus on issues that genuinely matter
+5. **Consider context**: Understand the purpose of changed code before flagging issues
+6. **Validate confidence**: If you're not >80% sure, don't report it
+7. **Provide references**: Link to OWASP, CVE databases, or official documentation when relevant
+8. **Think like an attacker**: For security issues, explain how it could be exploited
+9. **Be constructive**: Frame issues as opportunities to improve, not criticisms
+10. **Respect the diff**: Only review code that changed in this PR
+
+## Important Notes
+
+- If no issues found, return an empty array `[]`
+- **Maximum 10 findings** to avoid overwhelming developers
+- Prioritize: **security > correctness > quality > style**
+- Focus on **changed code only** (don't review unmodified lines unless context is critical)
+- When in doubt about severity, err on the side of **higher severity** for security issues
+- For critical findings, verify the issue exists and is exploitable before reporting
+
+## Example High-Quality Finding
+
+```json
+{
+ "id": "finding-auth-1",
+ "severity": "critical",
+ "category": "security",
+ "confidence": 0.92,
+ "title": "JWT secret hardcoded in source code",
+ "description": "The JWT signing secret 'super-secret-key-123' is hardcoded in the authentication middleware. Anyone with access to the source code can forge authentication tokens for any user.",
+ "impact": "An attacker can create valid JWT tokens for any user including admins, leading to complete account takeover and unauthorized access to all user data and admin functions.",
+ "file": "src/middleware/auth.ts",
+ "line": 12,
+ "code_snippet": "const SECRET = 'super-secret-key-123';\njwt.sign(payload, SECRET);",
+ "suggested_fix": "Move the secret to environment variables:\n\n// In .env file:\nJWT_SECRET=\n\n// In auth.ts:\nconst SECRET = process.env.JWT_SECRET;\nif (!SECRET) {\n throw new Error('JWT_SECRET not configured');\n}\njwt.sign(payload, SECRET);",
+ "fixable": true,
+ "references": [
+ "https://owasp.org/Top10/A02_2021-Cryptographic_Failures/",
+ "https://cheatsheetseries.owasp.org/cheatsheets/JSON_Web_Token_for_Java_Cheat_Sheet.html"
+ ]
+}
+```
+
+---
+
+Remember: Your goal is to find **genuine, high-impact issues** that will make the codebase more secure, correct, and maintainable. Quality over quantity. Be thorough but focused.
diff --git a/apps/backend/prompts/github/pr_security_agent.md b/apps/backend/prompts/github/pr_security_agent.md
new file mode 100644
index 00000000..7a72dfbc
--- /dev/null
+++ b/apps/backend/prompts/github/pr_security_agent.md
@@ -0,0 +1,161 @@
+# Security Review Agent
+
+You are a focused security review agent. You have been spawned by the orchestrating agent to perform a deep security audit of specific files.
+
+## Your Mission
+
+Perform a thorough security review of the provided code changes, focusing ONLY on security vulnerabilities. Do not review code quality, style, or other non-security concerns.
+
+## Security Focus Areas
+
+### 1. Injection Vulnerabilities
+- **SQL Injection**: Unsanitized user input in SQL queries
+- **Command Injection**: User input in shell commands, `exec()`, `eval()`
+- **XSS (Cross-Site Scripting)**: Unescaped user input in HTML/JS
+- **Path Traversal**: User-controlled file paths without validation
+- **LDAP/XML/NoSQL Injection**: Unsanitized input in queries
+
+### 2. Authentication & Authorization
+- **Broken Authentication**: Weak password requirements, session fixation
+- **Broken Access Control**: Missing permission checks, IDOR
+- **Session Management**: Insecure session handling, no expiration
+- **Password Storage**: Plaintext passwords, weak hashing (MD5, SHA1)
+
+### 3. Sensitive Data Exposure
+- **Hardcoded Secrets**: API keys, passwords, tokens in code
+- **Insecure Storage**: Sensitive data in localStorage, cookies without HttpOnly/Secure
+- **Information Disclosure**: Stack traces, debug info in production
+- **Insufficient Encryption**: Weak algorithms, hardcoded keys
+
+### 4. Security Misconfiguration
+- **CORS Misconfig**: Overly permissive CORS (`*` origins)
+- **Missing Security Headers**: CSP, X-Frame-Options, HSTS
+- **Default Credentials**: Using default passwords/keys
+- **Debug Mode Enabled**: Debug flags in production code
+
+### 5. Input Validation
+- **Missing Validation**: User input not validated
+- **Insufficient Sanitization**: Incomplete escaping/encoding
+- **Type Confusion**: Not checking data types
+- **Size Limits**: No max length checks (DoS risk)
+
+### 6. Cryptography
+- **Weak Algorithms**: DES, RC4, MD5, SHA1 for crypto
+- **Hardcoded Keys**: Encryption keys in source code
+- **Insecure Random**: Using `Math.random()` for security
+- **No Salt**: Password hashing without salt
+
+### 7. Third-Party Dependencies
+- **Known Vulnerabilities**: Using vulnerable package versions
+- **Untrusted Sources**: Installing from non-official registries
+- **Lack of Integrity Checks**: No checksums/signatures
+
+## Review Guidelines
+
+### High Confidence Only
+- Only report findings with **>80% confidence**
+- If you're unsure, don't report it
+- Prefer false negatives over false positives
+
+### Severity Classification
+- **CRITICAL**: Exploitable vulnerability leading to data breach, RCE, or system compromise
+ - Example: SQL injection, hardcoded admin password
+- **HIGH**: Serious security flaw that could be exploited
+ - Example: Missing authentication check, XSS vulnerability
+- **MEDIUM**: Security weakness that increases risk
+ - Example: Weak password requirements, missing security headers
+- **LOW**: Best practice violation, minimal risk
+ - Example: Using MD5 for non-security checksums
+
+### Contextual Analysis
+- Consider the application type (public API vs internal tool)
+- Check if mitigation exists elsewhere (e.g., WAF, input validation)
+- Review framework security features (does React escape by default?)
+
+## Code Patterns to Flag
+
+### JavaScript/TypeScript
+```javascript
+// CRITICAL: SQL Injection
+db.query(`SELECT * FROM users WHERE id = ${req.params.id}`);
+
+// CRITICAL: Command Injection
+exec(`git clone ${userInput}`);
+
+// HIGH: XSS
+el.innerHTML = userInput;
+
+// HIGH: Hardcoded secret
+const API_KEY = "sk-abc123...";
+
+// MEDIUM: Insecure random
+const token = Math.random().toString(36);
+```
+
+### Python
+```python
+# CRITICAL: SQL Injection
+cursor.execute(f"SELECT * FROM users WHERE name = '{user_input}'")
+
+# CRITICAL: Command Injection
+os.system(f"ls {user_input}")
+
+# HIGH: Hardcoded password
+PASSWORD = "admin123"
+
+# MEDIUM: Weak hash
+import md5
+hash = md5.md5(password).hexdigest()
+```
+
+### General Patterns
+- User input from: `req.params`, `req.query`, `req.body`, `request.GET`, `request.POST`
+- Dangerous functions: `eval()`, `exec()`, `dangerouslySetInnerHTML`, `os.system()`
+- Secrets in: Variable names with `password`, `secret`, `key`, `token`
+
+## Output Format
+
+Provide findings in JSON format:
+
+```json
+[
+ {
+ "file": "src/api/user.ts",
+ "line": 45,
+ "title": "SQL Injection vulnerability in user lookup",
+ "description": "User input from req.params.id is directly interpolated into SQL query without sanitization. An attacker could inject malicious SQL to extract sensitive data or modify the database.",
+ "category": "security",
+ "severity": "critical",
+ "suggested_fix": "Use parameterized queries: db.query('SELECT * FROM users WHERE id = ?', [req.params.id])",
+ "confidence": 95
+ },
+ {
+ "file": "src/auth/login.ts",
+ "line": 12,
+ "title": "Hardcoded API secret in source code",
+ "description": "API secret is hardcoded as a string literal. If this code is committed to version control, the secret is exposed to anyone with repository access.",
+ "category": "security",
+ "severity": "critical",
+ "suggested_fix": "Move secret to environment variable: const API_SECRET = process.env.API_SECRET",
+ "confidence": 100
+ }
+]
+```
+
+## Important Notes
+
+1. **Be Specific**: Include exact file path and line number
+2. **Explain Impact**: Describe what an attacker could do
+3. **Provide Fix**: Give actionable suggested_fix to remediate
+4. **Check Context**: Don't flag false positives (e.g., test files, mock data)
+5. **Focus on NEW Code**: Prioritize reviewing additions over deletions
+
+## Examples of What NOT to Report
+
+- Code style issues (use camelCase vs snake_case)
+- Performance concerns (inefficient loop)
+- Missing comments or documentation
+- Complex code that's hard to understand
+- Test files with mock secrets (unless it's a real secret!)
+
+Focus on **security vulnerabilities** only. High confidence, high impact findings.
diff --git a/apps/backend/prompts/github/pr_structural.md b/apps/backend/prompts/github/pr_structural.md
new file mode 100644
index 00000000..81871a48
--- /dev/null
+++ b/apps/backend/prompts/github/pr_structural.md
@@ -0,0 +1,171 @@
+# Structural PR Review Agent
+
+## Your Role
+
+You are a senior software architect reviewing this PR for **structural issues** that automated code analysis tools typically miss. Your focus is on:
+
+1. **Feature Creep** - Does the PR do more than what was asked?
+2. **Scope Coherence** - Are all changes working toward the same goal?
+3. **Architecture Alignment** - Does this fit established patterns?
+4. **PR Structure Quality** - Is this PR sized and organized well?
+
+## Review Methodology
+
+For each structural concern:
+
+1. **Understand the PR's stated purpose** - Read the title and description carefully
+2. **Analyze what the code actually changes** - Map all modifications
+3. **Compare intent vs implementation** - Look for scope mismatch
+4. **Assess architectural fit** - Does this follow existing patterns?
+5. **Apply the 80% confidence threshold** - Only report confident findings
+
+## Structural Issue Categories
+
+### 1. Feature Creep Detection
+
+**Look for signs of scope expansion:**
+
+- PR titled "Fix login bug" but also refactors unrelated components
+- "Add button to X" but includes new database models
+- "Update styles" but changes business logic
+- Bundled "while I'm here" changes unrelated to the main goal
+- New dependencies added for functionality beyond the PR's scope
+
+**Questions to ask:**
+
+- Does every file change directly support the PR's stated goal?
+- Are there changes that would make sense as a separate PR?
+- Is the PR trying to accomplish multiple distinct objectives?
+
+### 2. Scope Coherence Analysis
+
+**Look for:**
+
+- **Contradictory changes**: One file does X while another undoes X
+- **Orphaned code**: New code added but never called/used
+- **Incomplete features**: Started but not finished functionality
+- **Mixed concerns**: UI changes bundled with backend logic changes
+- **Unrelated test changes**: Tests modified for features not in this PR
+
+### 3. Architecture Alignment
+
+**Check for violations:**
+
+- **Pattern consistency**: Does new code follow established patterns?
+ - If the project uses services/repositories, does new code follow that?
+ - If the project has a specific file organization, is it respected?
+- **Separation of concerns**: Is business logic mixing with presentation?
+- **Dependency direction**: Are dependencies going the wrong way?
+ - Lower layers depending on higher layers
+ - Core modules importing from UI modules
+- **Technology alignment**: Using different tech stack than established
+
+### 4. PR Structure Quality
+
+**Evaluate:**
+
+- **Size assessment**:
+ - <100 lines: Good, easy to review
+ - 100-300 lines: Acceptable
+ - 300-500 lines: Consider splitting
+ - >500 lines: Should definitely be split (unless a single new file)
+
+- **Commit organization**:
+ - Are commits logically grouped?
+ - Do commit messages describe the changes accurately?
+ - Could commits be squashed or reorganized for clarity?
+
+- **Atomicity**:
+ - Is this a single logical change?
+ - Could this be reverted cleanly if needed?
+ - Are there interdependent changes that should be split?
+
+## Severity Guidelines
+
+### Critical
+- Architectural violations that will cause maintenance nightmares
+- Feature creep introducing untested, unplanned functionality
+- Changes that fundamentally don't fit the codebase
+
+### High
+- Significant scope creep (>30% of changes unrelated to PR goal)
+- Breaking established patterns without justification
+- PR should definitely be split (>500 lines with distinct features)
+
+### Medium
+- Minor scope creep (changes could be separate but are related)
+- Inconsistent pattern usage (not breaking, just inconsistent)
+- PR could benefit from splitting (300-500 lines)
+
+### Low
+- Commit organization could be improved
+- Minor naming inconsistencies with codebase conventions
+- Optional cleanup suggestions
+
+## Output Format
+
+Return a JSON array of structural issues:
+
+```json
+[
+ {
+ "id": "struct-1",
+ "issue_type": "feature_creep",
+ "severity": "high",
+ "title": "PR includes unrelated authentication refactor",
+ "description": "The PR is titled 'Fix payment validation bug' but includes a complete refactor of the authentication middleware (files auth.ts, session.ts). These changes are unrelated to payment validation and add 200+ lines to the review.",
+ "impact": "Bundles unrelated changes make review harder, increase merge conflict risk, and make git blame/bisect less useful. If the auth changes introduce bugs, reverting will also revert the payment fix.",
+ "suggestion": "Split into two PRs:\n1. 'Fix payment validation bug' (current files: payment.ts, validation.ts)\n2. 'Refactor authentication middleware' (auth.ts, session.ts)\n\nThis allows each change to be reviewed, tested, and deployed independently."
+ },
+ {
+ "id": "struct-2",
+ "issue_type": "architecture_violation",
+ "severity": "medium",
+ "title": "UI component directly imports database module",
+ "description": "The UserCard.tsx component directly imports and calls db.query(). The codebase uses a service layer pattern where UI components should only interact with services.",
+ "impact": "Bypassing the service layer creates tight coupling between UI and database, makes testing harder, and violates the established separation of concerns.",
+ "suggestion": "Create or use an existing UserService to handle the data fetching:\n\n// UserService.ts\nexport const UserService = {\n getUserById: async (id: string) => db.query(...)\n};\n\n// UserCard.tsx\nimport { UserService } from './services/UserService';\nconst user = await UserService.getUserById(id);"
+ },
+ {
+ "id": "struct-3",
+ "issue_type": "scope_creep",
+ "severity": "low",
+ "title": "Unrelated console.log cleanup bundled with feature",
+ "description": "Several console.log statements were removed from files unrelated to the main feature (utils.ts, config.ts). While cleanup is good, bundling it obscures the main changes.",
+ "impact": "Minor: Makes the diff larger and slightly harder to focus on the main change.",
+ "suggestion": "Consider keeping unrelated cleanup in a separate 'chore: remove debug logs' commit or PR."
+ }
+]
+```
+
+## Field Definitions
+
+- **id**: Unique identifier (e.g., "struct-1", "struct-2")
+- **issue_type**: One of:
+ - `feature_creep` - PR does more than stated
+ - `scope_creep` - Related but should be separate changes
+ - `architecture_violation` - Breaks established patterns
+ - `poor_structure` - PR organization issues (size, commits, atomicity)
+- **severity**: `critical` | `high` | `medium` | `low`
+- **title**: Short, specific summary (max 80 chars)
+- **description**: Detailed explanation with specific examples
+- **impact**: Why this matters (maintenance, review quality, risk)
+- **suggestion**: Actionable recommendation to address the issue
+
+## Guidelines
+
+1. **Read the PR title and description first** - Understand stated intent
+2. **Map all changes** - List what files/areas are modified
+3. **Compare intent vs changes** - Look for mismatch
+4. **Check patterns** - Compare to existing codebase structure
+5. **Be constructive** - Suggest how to improve, not just criticize
+6. **Maximum 5 issues** - Focus on most impactful structural concerns
+7. **80% confidence threshold** - Only report clear structural issues
+
+## Important Notes
+
+- If PR is well-structured, return an empty array `[]`
+- Focus on **structural** issues, not code quality or security (those are separate passes)
+- Consider the **developer's perspective** - these issues should help them ship better
+- Large PRs aren't always bad - a single new feature file of 600 lines may be fine
+- Judge scope relative to the **PR's stated purpose**, not absolute rules
diff --git a/apps/backend/prompts/github/spam_detector.md b/apps/backend/prompts/github/spam_detector.md
new file mode 100644
index 00000000..950da87d
--- /dev/null
+++ b/apps/backend/prompts/github/spam_detector.md
@@ -0,0 +1,110 @@
+# Spam Issue Detector
+
+You are a spam detection specialist for GitHub issues. Your task is to identify spam, troll content, and low-quality issues that don't warrant developer attention.
+
+## Spam Categories
+
+### Promotional Spam
+- Product advertisements
+- Service promotions
+- Affiliate links
+- SEO manipulation attempts
+- Cryptocurrency/NFT promotions
+
+### Abuse & Trolling
+- Offensive language or slurs
+- Personal attacks
+- Harassment content
+- Intentionally disruptive content
+- Repeated off-topic submissions
+
+### Low-Quality Content
+- Random characters or gibberish
+- Test submissions ("test", "asdf")
+- Empty or near-empty issues
+- Completely unrelated content
+- Auto-generated nonsense
+
+### Bot/Mass Submissions
+- Template-based mass submissions
+- Automated security scanner output (without context)
+- Generic "found a bug" without details
+- Suspiciously similar to other recent issues
+
+## Detection Signals
+
+### High-Confidence Spam Indicators
+- External promotional links
+- No relation to project
+- Offensive content
+- Gibberish text
+- Known spam patterns
+
+### Medium-Confidence Indicators
+- Very short, vague content
+- No technical details
+- Generic language (could be new user)
+- Suspicious links
+
+### Low-Confidence Indicators
+- Unusual formatting
+- Non-English content (could be legitimate)
+- First-time contributor (not spam indicator alone)
+
+## Analysis Process
+
+1. **Content Analysis**: Check for promotional/offensive content
+2. **Link Analysis**: Evaluate any external links
+3. **Pattern Matching**: Check against known spam patterns
+4. **Context Check**: Is this related to the project at all?
+5. **Author Check**: New account with suspicious activity
+
+## Output Format
+
+```json
+{
+ "is_spam": true,
+ "confidence": 0.95,
+ "spam_type": "promotional",
+ "indicators": [
+ "Contains promotional link to unrelated product",
+ "No reference to project functionality",
+ "Generic marketing language"
+ ],
+ "recommendation": "flag_for_review",
+ "explanation": "This issue contains a promotional link to an unrelated cryptocurrency trading platform with no connection to the project."
+}
+```
+
+## Spam Types
+
+- `promotional`: Advertising/marketing content
+- `abuse`: Offensive or harassing content
+- `gibberish`: Random/meaningless text
+- `bot_generated`: Automated spam submissions
+- `off_topic`: Completely unrelated to project
+- `test_submission`: Test/placeholder content
+
+## Recommendations
+
+- `flag_for_review`: Add label, wait for human decision
+- `needs_more_info`: Could be legitimate, needs clarification
+- `likely_legitimate`: Low confidence, probably not spam
+
+## Important Guidelines
+
+1. **Never auto-close**: Always flag for human review
+2. **Consider new users**: First issues may be poorly formatted
+3. **Language barriers**: Non-English ≠ spam
+4. **False positives are worse**: When in doubt, don't flag
+5. **No engagement**: Don't respond to obvious spam
+6. **Be respectful**: Even unclear issues might be genuine
+
+## Not Spam (Common False Positives)
+
+- Poorly written but genuine bug reports
+- Non-English issues (unless gibberish)
+- Issues with external links to relevant tools
+- First-time contributors with formatting issues
+- Automated test result submissions from CI
+- Issues from legitimate security researchers
diff --git a/apps/backend/runners/github/__init__.py b/apps/backend/runners/github/__init__.py
new file mode 100644
index 00000000..0239d9e1
--- /dev/null
+++ b/apps/backend/runners/github/__init__.py
@@ -0,0 +1,41 @@
+"""
+GitHub Automation Runners
+=========================
+
+Standalone runner system for GitHub automation:
+- PR Review: AI-powered code review with fix suggestions
+- Issue Triage: Duplicate/spam/feature-creep detection
+- Issue Auto-Fix: Automatic spec creation and execution from issues
+
+This is SEPARATE from the main task execution pipeline (spec_runner, run.py, etc.)
+to maintain modularity and avoid breaking existing features.
+"""
+
+from .models import (
+ AutoFixState,
+ AutoFixStatus,
+ GitHubRunnerConfig,
+ PRReviewFinding,
+ PRReviewResult,
+ ReviewCategory,
+ ReviewSeverity,
+ TriageCategory,
+ TriageResult,
+)
+from .orchestrator import GitHubOrchestrator
+
+__all__ = [
+ # Orchestrator
+ "GitHubOrchestrator",
+ # Models
+ "PRReviewResult",
+ "PRReviewFinding",
+ "TriageResult",
+ "AutoFixState",
+ "GitHubRunnerConfig",
+ # Enums
+ "ReviewSeverity",
+ "ReviewCategory",
+ "TriageCategory",
+ "AutoFixStatus",
+]
diff --git a/apps/backend/runners/github/audit.py b/apps/backend/runners/github/audit.py
new file mode 100644
index 00000000..4f0172fa
--- /dev/null
+++ b/apps/backend/runners/github/audit.py
@@ -0,0 +1,738 @@
+"""
+GitHub Automation Audit Logger
+==============================
+
+Structured audit logging for all GitHub automation operations.
+Provides compliance trail, debugging support, and security audit capabilities.
+
+Features:
+- JSON-formatted structured logs
+- Correlation ID generation per operation
+- Actor tracking (user/bot/automation)
+- Duration and token usage tracking
+- Log rotation with configurable retention
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import time
+import uuid
+from contextlib import contextmanager
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from enum import Enum
+from pathlib import Path
+from typing import Any
+
+# Configure module logger
+logger = logging.getLogger(__name__)
+
+
+class AuditAction(str, Enum):
+ """Types of auditable actions."""
+
+ # PR Review actions
+ PR_REVIEW_STARTED = "pr_review_started"
+ PR_REVIEW_COMPLETED = "pr_review_completed"
+ PR_REVIEW_FAILED = "pr_review_failed"
+ PR_REVIEW_POSTED = "pr_review_posted"
+
+ # Issue Triage actions
+ TRIAGE_STARTED = "triage_started"
+ TRIAGE_COMPLETED = "triage_completed"
+ TRIAGE_FAILED = "triage_failed"
+ LABELS_APPLIED = "labels_applied"
+
+ # Auto-fix actions
+ AUTOFIX_STARTED = "autofix_started"
+ AUTOFIX_SPEC_CREATED = "autofix_spec_created"
+ AUTOFIX_BUILD_STARTED = "autofix_build_started"
+ AUTOFIX_PR_CREATED = "autofix_pr_created"
+ AUTOFIX_COMPLETED = "autofix_completed"
+ AUTOFIX_FAILED = "autofix_failed"
+ AUTOFIX_CANCELLED = "autofix_cancelled"
+
+ # Permission actions
+ PERMISSION_GRANTED = "permission_granted"
+ PERMISSION_DENIED = "permission_denied"
+ TOKEN_VERIFIED = "token_verified"
+
+ # Bot detection actions
+ BOT_DETECTED = "bot_detected"
+ REVIEW_SKIPPED = "review_skipped"
+
+ # Rate limiting actions
+ RATE_LIMIT_WARNING = "rate_limit_warning"
+ RATE_LIMIT_EXCEEDED = "rate_limit_exceeded"
+ COST_LIMIT_WARNING = "cost_limit_warning"
+ COST_LIMIT_EXCEEDED = "cost_limit_exceeded"
+
+ # GitHub API actions
+ GITHUB_API_CALL = "github_api_call"
+ GITHUB_API_ERROR = "github_api_error"
+ GITHUB_API_TIMEOUT = "github_api_timeout"
+
+ # AI Agent actions
+ AI_AGENT_STARTED = "ai_agent_started"
+ AI_AGENT_COMPLETED = "ai_agent_completed"
+ AI_AGENT_FAILED = "ai_agent_failed"
+
+ # Override actions
+ OVERRIDE_APPLIED = "override_applied"
+ CANCEL_REQUESTED = "cancel_requested"
+
+ # State transitions
+ STATE_TRANSITION = "state_transition"
+
+
+class ActorType(str, Enum):
+ """Types of actors that can trigger actions."""
+
+ USER = "user"
+ BOT = "bot"
+ AUTOMATION = "automation"
+ SYSTEM = "system"
+ WEBHOOK = "webhook"
+
+
+@dataclass
+class AuditContext:
+ """Context for an auditable operation."""
+
+ correlation_id: str
+ actor_type: ActorType
+ actor_id: str | None = None
+ repo: str | None = None
+ pr_number: int | None = None
+ issue_number: int | None = None
+ started_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
+ metadata: dict[str, Any] = field(default_factory=dict)
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "correlation_id": self.correlation_id,
+ "actor_type": self.actor_type.value,
+ "actor_id": self.actor_id,
+ "repo": self.repo,
+ "pr_number": self.pr_number,
+ "issue_number": self.issue_number,
+ "started_at": self.started_at.isoformat(),
+ "metadata": self.metadata,
+ }
+
+
+@dataclass
+class AuditEntry:
+ """A single audit log entry."""
+
+ timestamp: datetime
+ correlation_id: str
+ action: AuditAction
+ actor_type: ActorType
+ actor_id: str | None
+ repo: str | None
+ pr_number: int | None
+ issue_number: int | None
+ result: str # success, failure, skipped
+ duration_ms: int | None
+ error: str | None
+ details: dict[str, Any]
+ token_usage: dict[str, int] | None # input_tokens, output_tokens
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "timestamp": self.timestamp.isoformat(),
+ "correlation_id": self.correlation_id,
+ "action": self.action.value,
+ "actor_type": self.actor_type.value,
+ "actor_id": self.actor_id,
+ "repo": self.repo,
+ "pr_number": self.pr_number,
+ "issue_number": self.issue_number,
+ "result": self.result,
+ "duration_ms": self.duration_ms,
+ "error": self.error,
+ "details": self.details,
+ "token_usage": self.token_usage,
+ }
+
+ def to_json(self) -> str:
+ return json.dumps(self.to_dict(), default=str)
+
+
+class AuditLogger:
+ """
+ Structured audit logger for GitHub automation.
+
+ Usage:
+ audit = AuditLogger(log_dir=Path(".auto-claude/github/audit"))
+
+ # Start an operation with context
+ ctx = audit.start_operation(
+ actor_type=ActorType.USER,
+ actor_id="username",
+ repo="owner/repo",
+ pr_number=123,
+ )
+
+ # Log events during the operation
+ audit.log(ctx, AuditAction.PR_REVIEW_STARTED)
+
+ # ... do work ...
+
+ # Log completion with details
+ audit.log(
+ ctx,
+ AuditAction.PR_REVIEW_COMPLETED,
+ result="success",
+ details={"findings_count": 5},
+ )
+ """
+
+ _instance: AuditLogger | None = None
+
+ def __init__(
+ self,
+ log_dir: Path | None = None,
+ retention_days: int = 30,
+ max_file_size_mb: int = 100,
+ enabled: bool = True,
+ ):
+ """
+ Initialize audit logger.
+
+ Args:
+ log_dir: Directory for audit logs (default: .auto-claude/github/audit)
+ retention_days: Days to retain logs (default: 30)
+ max_file_size_mb: Max size per log file before rotation (default: 100MB)
+ enabled: Whether audit logging is enabled (default: True)
+ """
+ self.log_dir = log_dir or Path(".auto-claude/github/audit")
+ self.retention_days = retention_days
+ self.max_file_size_mb = max_file_size_mb
+ self.enabled = enabled
+
+ if enabled:
+ self.log_dir.mkdir(parents=True, exist_ok=True)
+ self._current_log_file: Path | None = None
+ self._rotate_if_needed()
+
+ @classmethod
+ def get_instance(
+ cls,
+ log_dir: Path | None = None,
+ **kwargs,
+ ) -> AuditLogger:
+ """Get or create singleton instance."""
+ if cls._instance is None:
+ cls._instance = cls(log_dir=log_dir, **kwargs)
+ return cls._instance
+
+ @classmethod
+ def reset_instance(cls) -> None:
+ """Reset singleton (for testing)."""
+ cls._instance = None
+
+ def _get_log_file_path(self) -> Path:
+ """Get path for current day's log file."""
+ date_str = datetime.now(timezone.utc).strftime("%Y-%m-%d")
+ return self.log_dir / f"audit_{date_str}.jsonl"
+
+ def _rotate_if_needed(self) -> None:
+ """Rotate log file if it exceeds max size."""
+ if not self.enabled:
+ return
+
+ log_file = self._get_log_file_path()
+
+ if log_file.exists():
+ size_mb = log_file.stat().st_size / (1024 * 1024)
+ if size_mb >= self.max_file_size_mb:
+ # Rotate: add timestamp suffix
+ timestamp = datetime.now(timezone.utc).strftime("%H%M%S")
+ rotated = log_file.with_suffix(f".{timestamp}.jsonl")
+ log_file.rename(rotated)
+ logger.info(f"Rotated audit log to {rotated}")
+
+ self._current_log_file = log_file
+
+ def _cleanup_old_logs(self) -> None:
+ """Remove logs older than retention period."""
+ if not self.enabled or not self.log_dir.exists():
+ return
+
+ cutoff = datetime.now(timezone.utc).timestamp() - (
+ self.retention_days * 24 * 60 * 60
+ )
+
+ for log_file in self.log_dir.glob("audit_*.jsonl"):
+ if log_file.stat().st_mtime < cutoff:
+ log_file.unlink()
+ logger.info(f"Deleted old audit log: {log_file}")
+
+ def generate_correlation_id(self) -> str:
+ """Generate a unique correlation ID for an operation."""
+ return f"gh-{uuid.uuid4().hex[:12]}"
+
+ def start_operation(
+ self,
+ actor_type: ActorType,
+ actor_id: str | None = None,
+ repo: str | None = None,
+ pr_number: int | None = None,
+ issue_number: int | None = None,
+ correlation_id: str | None = None,
+ metadata: dict[str, Any] | None = None,
+ ) -> AuditContext:
+ """
+ Start a new auditable operation.
+
+ Args:
+ actor_type: Type of actor (USER, BOT, AUTOMATION, SYSTEM)
+ actor_id: Identifier for the actor (username, bot name, etc.)
+ repo: Repository in owner/repo format
+ pr_number: PR number if applicable
+ issue_number: Issue number if applicable
+ correlation_id: Optional existing correlation ID
+ metadata: Additional context metadata
+
+ Returns:
+ AuditContext for use with log() calls
+ """
+ return AuditContext(
+ correlation_id=correlation_id or self.generate_correlation_id(),
+ actor_type=actor_type,
+ actor_id=actor_id,
+ repo=repo,
+ pr_number=pr_number,
+ issue_number=issue_number,
+ metadata=metadata or {},
+ )
+
+ def log(
+ self,
+ context: AuditContext,
+ action: AuditAction,
+ result: str = "success",
+ error: str | None = None,
+ details: dict[str, Any] | None = None,
+ token_usage: dict[str, int] | None = None,
+ duration_ms: int | None = None,
+ ) -> AuditEntry:
+ """
+ Log an audit event.
+
+ Args:
+ context: Audit context from start_operation()
+ action: The action being logged
+ result: Result status (success, failure, skipped)
+ error: Error message if failed
+ details: Additional details about the action
+ token_usage: Token usage if AI-related (input_tokens, output_tokens)
+ duration_ms: Duration in milliseconds if timed
+
+ Returns:
+ The created AuditEntry
+ """
+ # Calculate duration from context start if not provided
+ if duration_ms is None and context.started_at:
+ elapsed = datetime.now(timezone.utc) - context.started_at
+ duration_ms = int(elapsed.total_seconds() * 1000)
+
+ entry = AuditEntry(
+ timestamp=datetime.now(timezone.utc),
+ correlation_id=context.correlation_id,
+ action=action,
+ actor_type=context.actor_type,
+ actor_id=context.actor_id,
+ repo=context.repo,
+ pr_number=context.pr_number,
+ issue_number=context.issue_number,
+ result=result,
+ duration_ms=duration_ms,
+ error=error,
+ details=details or {},
+ token_usage=token_usage,
+ )
+
+ self._write_entry(entry)
+ return entry
+
+ def _write_entry(self, entry: AuditEntry) -> None:
+ """Write an entry to the log file."""
+ if not self.enabled:
+ return
+
+ self._rotate_if_needed()
+
+ try:
+ log_file = self._get_log_file_path()
+ with open(log_file, "a") as f:
+ f.write(entry.to_json() + "\n")
+ except Exception as e:
+ logger.error(f"Failed to write audit log: {e}")
+
+ @contextmanager
+ def operation(
+ self,
+ action_start: AuditAction,
+ action_complete: AuditAction,
+ action_failed: AuditAction,
+ actor_type: ActorType,
+ actor_id: str | None = None,
+ repo: str | None = None,
+ pr_number: int | None = None,
+ issue_number: int | None = None,
+ metadata: dict[str, Any] | None = None,
+ ):
+ """
+ Context manager for auditing an operation.
+
+ Usage:
+ with audit.operation(
+ action_start=AuditAction.PR_REVIEW_STARTED,
+ action_complete=AuditAction.PR_REVIEW_COMPLETED,
+ action_failed=AuditAction.PR_REVIEW_FAILED,
+ actor_type=ActorType.AUTOMATION,
+ repo="owner/repo",
+ pr_number=123,
+ ) as ctx:
+ # Do work
+ ctx.metadata["findings_count"] = 5
+
+ Automatically logs start, completion, and failure with timing.
+ """
+ ctx = self.start_operation(
+ actor_type=actor_type,
+ actor_id=actor_id,
+ repo=repo,
+ pr_number=pr_number,
+ issue_number=issue_number,
+ metadata=metadata,
+ )
+
+ self.log(ctx, action_start, result="started")
+ start_time = time.monotonic()
+
+ try:
+ yield ctx
+ duration_ms = int((time.monotonic() - start_time) * 1000)
+ self.log(
+ ctx,
+ action_complete,
+ result="success",
+ details=ctx.metadata,
+ duration_ms=duration_ms,
+ )
+ except Exception as e:
+ duration_ms = int((time.monotonic() - start_time) * 1000)
+ self.log(
+ ctx,
+ action_failed,
+ result="failure",
+ error=str(e),
+ details=ctx.metadata,
+ duration_ms=duration_ms,
+ )
+ raise
+
+ def log_github_api_call(
+ self,
+ context: AuditContext,
+ endpoint: str,
+ method: str = "GET",
+ status_code: int | None = None,
+ duration_ms: int | None = None,
+ error: str | None = None,
+ ) -> None:
+ """Log a GitHub API call."""
+ action = (
+ AuditAction.GITHUB_API_CALL if not error else AuditAction.GITHUB_API_ERROR
+ )
+ self.log(
+ context,
+ action,
+ result="success" if not error else "failure",
+ error=error,
+ details={
+ "endpoint": endpoint,
+ "method": method,
+ "status_code": status_code,
+ },
+ duration_ms=duration_ms,
+ )
+
+ def log_ai_agent(
+ self,
+ context: AuditContext,
+ agent_type: str,
+ model: str,
+ input_tokens: int | None = None,
+ output_tokens: int | None = None,
+ duration_ms: int | None = None,
+ error: str | None = None,
+ ) -> None:
+ """Log an AI agent invocation."""
+ action = (
+ AuditAction.AI_AGENT_COMPLETED if not error else AuditAction.AI_AGENT_FAILED
+ )
+ self.log(
+ context,
+ action,
+ result="success" if not error else "failure",
+ error=error,
+ details={
+ "agent_type": agent_type,
+ "model": model,
+ },
+ token_usage={
+ "input_tokens": input_tokens or 0,
+ "output_tokens": output_tokens or 0,
+ },
+ duration_ms=duration_ms,
+ )
+
+ def log_permission_check(
+ self,
+ context: AuditContext,
+ allowed: bool,
+ reason: str,
+ username: str | None = None,
+ role: str | None = None,
+ ) -> None:
+ """Log a permission check result."""
+ action = (
+ AuditAction.PERMISSION_GRANTED if allowed else AuditAction.PERMISSION_DENIED
+ )
+ self.log(
+ context,
+ action,
+ result="granted" if allowed else "denied",
+ details={
+ "reason": reason,
+ "username": username,
+ "role": role,
+ },
+ )
+
+ def log_state_transition(
+ self,
+ context: AuditContext,
+ from_state: str,
+ to_state: str,
+ reason: str | None = None,
+ ) -> None:
+ """Log a state machine transition."""
+ self.log(
+ context,
+ AuditAction.STATE_TRANSITION,
+ details={
+ "from_state": from_state,
+ "to_state": to_state,
+ "reason": reason,
+ },
+ )
+
+ def log_override(
+ self,
+ context: AuditContext,
+ override_type: str,
+ original_action: str,
+ actor_id: str,
+ ) -> None:
+ """Log a user override action."""
+ self.log(
+ context,
+ AuditAction.OVERRIDE_APPLIED,
+ details={
+ "override_type": override_type,
+ "original_action": original_action,
+ "overridden_by": actor_id,
+ },
+ )
+
+ def query_logs(
+ self,
+ correlation_id: str | None = None,
+ action: AuditAction | None = None,
+ repo: str | None = None,
+ pr_number: int | None = None,
+ issue_number: int | None = None,
+ since: datetime | None = None,
+ limit: int = 100,
+ ) -> list[AuditEntry]:
+ """
+ Query audit logs with filters.
+
+ Args:
+ correlation_id: Filter by correlation ID
+ action: Filter by action type
+ repo: Filter by repository
+ pr_number: Filter by PR number
+ issue_number: Filter by issue number
+ since: Only entries after this time
+ limit: Maximum entries to return
+
+ Returns:
+ List of matching AuditEntry objects
+ """
+ if not self.enabled or not self.log_dir.exists():
+ return []
+
+ results = []
+
+ for log_file in sorted(self.log_dir.glob("audit_*.jsonl"), reverse=True):
+ try:
+ with open(log_file) as f:
+ for line in f:
+ if not line.strip():
+ continue
+
+ try:
+ data = json.loads(line)
+ except json.JSONDecodeError:
+ continue
+
+ # Apply filters
+ if (
+ correlation_id
+ and data.get("correlation_id") != correlation_id
+ ):
+ continue
+ if action and data.get("action") != action.value:
+ continue
+ if repo and data.get("repo") != repo:
+ continue
+ if pr_number and data.get("pr_number") != pr_number:
+ continue
+ if issue_number and data.get("issue_number") != issue_number:
+ continue
+ if since:
+ entry_time = datetime.fromisoformat(data["timestamp"])
+ if entry_time < since:
+ continue
+
+ # Reconstruct entry
+ entry = AuditEntry(
+ timestamp=datetime.fromisoformat(data["timestamp"]),
+ correlation_id=data["correlation_id"],
+ action=AuditAction(data["action"]),
+ actor_type=ActorType(data["actor_type"]),
+ actor_id=data.get("actor_id"),
+ repo=data.get("repo"),
+ pr_number=data.get("pr_number"),
+ issue_number=data.get("issue_number"),
+ result=data["result"],
+ duration_ms=data.get("duration_ms"),
+ error=data.get("error"),
+ details=data.get("details", {}),
+ token_usage=data.get("token_usage"),
+ )
+ results.append(entry)
+
+ if len(results) >= limit:
+ return results
+
+ except Exception as e:
+ logger.error(f"Error reading audit log {log_file}: {e}")
+
+ return results
+
+ def get_operation_history(self, correlation_id: str) -> list[AuditEntry]:
+ """Get all entries for a specific operation by correlation ID."""
+ return self.query_logs(correlation_id=correlation_id, limit=1000)
+
+ def get_statistics(
+ self,
+ repo: str | None = None,
+ since: datetime | None = None,
+ ) -> dict[str, Any]:
+ """
+ Get aggregate statistics from audit logs.
+
+ Returns:
+ Dictionary with counts by action, result, and actor type
+ """
+ entries = self.query_logs(repo=repo, since=since, limit=10000)
+
+ stats = {
+ "total_entries": len(entries),
+ "by_action": {},
+ "by_result": {},
+ "by_actor_type": {},
+ "total_duration_ms": 0,
+ "total_input_tokens": 0,
+ "total_output_tokens": 0,
+ }
+
+ for entry in entries:
+ # Count by action
+ action = entry.action.value
+ stats["by_action"][action] = stats["by_action"].get(action, 0) + 1
+
+ # Count by result
+ result = entry.result
+ stats["by_result"][result] = stats["by_result"].get(result, 0) + 1
+
+ # Count by actor type
+ actor = entry.actor_type.value
+ stats["by_actor_type"][actor] = stats["by_actor_type"].get(actor, 0) + 1
+
+ # Sum durations
+ if entry.duration_ms:
+ stats["total_duration_ms"] += entry.duration_ms
+
+ # Sum token usage
+ if entry.token_usage:
+ stats["total_input_tokens"] += entry.token_usage.get("input_tokens", 0)
+ stats["total_output_tokens"] += entry.token_usage.get(
+ "output_tokens", 0
+ )
+
+ return stats
+
+
+# Convenience functions for quick logging
+def get_audit_logger() -> AuditLogger:
+ """Get the global audit logger instance."""
+ return AuditLogger.get_instance()
+
+
+def audit_operation(
+ action_start: AuditAction,
+ action_complete: AuditAction,
+ action_failed: AuditAction,
+ **kwargs,
+):
+ """Decorator for auditing function calls."""
+
+ def decorator(func):
+ async def async_wrapper(*args, **func_kwargs):
+ audit = get_audit_logger()
+ with audit.operation(
+ action_start=action_start,
+ action_complete=action_complete,
+ action_failed=action_failed,
+ **kwargs,
+ ) as ctx:
+ return await func(*args, audit_context=ctx, **func_kwargs)
+
+ def sync_wrapper(*args, **func_kwargs):
+ audit = get_audit_logger()
+ with audit.operation(
+ action_start=action_start,
+ action_complete=action_complete,
+ action_failed=action_failed,
+ **kwargs,
+ ) as ctx:
+ return func(*args, audit_context=ctx, **func_kwargs)
+
+ import asyncio
+
+ if asyncio.iscoroutinefunction(func):
+ return async_wrapper
+ return sync_wrapper
+
+ return decorator
diff --git a/apps/backend/runners/github/batch_issues.py b/apps/backend/runners/github/batch_issues.py
new file mode 100644
index 00000000..765c689e
--- /dev/null
+++ b/apps/backend/runners/github/batch_issues.py
@@ -0,0 +1,1182 @@
+"""
+Issue Batching Service
+======================
+
+Groups similar issues together for combined auto-fix:
+- Uses semantic similarity from duplicates.py
+- Creates issue clusters using agglomerative clustering
+- Generates combined specs for issue batches
+- Tracks batch state and progress
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from enum import Enum
+from pathlib import Path
+from typing import Any
+
+logger = logging.getLogger(__name__)
+
+# Import validators
+try:
+ from .batch_validator import BatchValidator
+ from .duplicates import SIMILAR_THRESHOLD
+ from .file_lock import locked_json_write
+except (ImportError, ValueError, SystemError):
+ from batch_validator import BatchValidator
+ from duplicates import SIMILAR_THRESHOLD
+ from file_lock import locked_json_write
+
+
+class ClaudeBatchAnalyzer:
+ """
+ Claude-based batch analyzer for GitHub issues.
+
+ Instead of doing O(n²) pairwise comparisons, this uses a single Claude call
+ to analyze a group of issues and suggest optimal batching.
+ """
+
+ def __init__(self, project_dir: Path | None = None):
+ """Initialize Claude batch analyzer."""
+ self.project_dir = project_dir or Path.cwd()
+ logger.info(
+ f"[BATCH_ANALYZER] Initialized with project_dir: {self.project_dir}"
+ )
+
+ async def analyze_and_batch_issues(
+ self,
+ issues: list[dict[str, Any]],
+ max_batch_size: int = 5,
+ ) -> list[dict[str, Any]]:
+ """
+ Analyze a group of issues and suggest optimal batches.
+
+ Uses a SINGLE Claude call to analyze all issues and group them intelligently.
+
+ Args:
+ issues: List of issues to analyze
+ max_batch_size: Maximum issues per batch
+
+ Returns:
+ List of batch suggestions, each containing:
+ - issue_numbers: list of issue numbers in this batch
+ - theme: common theme/description
+ - reasoning: why these should be batched
+ - confidence: 0.0-1.0
+ """
+ if not issues:
+ return []
+
+ if len(issues) == 1:
+ # Single issue = single batch
+ return [
+ {
+ "issue_numbers": [issues[0]["number"]],
+ "theme": issues[0].get("title", "Single issue"),
+ "reasoning": "Single issue in group",
+ "confidence": 1.0,
+ }
+ ]
+
+ try:
+ import sys
+
+ from claude_agent_sdk import ClaudeAgentOptions, ClaudeSDKClient
+
+ backend_path = Path(__file__).parent.parent.parent
+ sys.path.insert(0, str(backend_path))
+ from core.auth import ensure_claude_code_oauth_token
+ except ImportError as e:
+ logger.error(f"claude-agent-sdk not available: {e}")
+ # Fallback: each issue is its own batch
+ return [
+ {
+ "issue_numbers": [issue["number"]],
+ "theme": issue.get("title", ""),
+ "reasoning": "Claude SDK not available",
+ "confidence": 0.5,
+ }
+ for issue in issues
+ ]
+
+ # Build issue list for the prompt
+ issue_list = "\n".join(
+ [
+ f"- #{issue['number']}: {issue.get('title', 'No title')}"
+ f"\n Labels: {', '.join(label.get('name', '') for label in issue.get('labels', [])) or 'none'}"
+ f"\n Body: {(issue.get('body', '') or '')[:200]}..."
+ for issue in issues
+ ]
+ )
+
+ prompt = f"""Analyze these GitHub issues and group them into batches that should be fixed together.
+
+ISSUES TO ANALYZE:
+{issue_list}
+
+RULES:
+1. Group issues that share a common root cause or affect the same component
+2. Maximum {max_batch_size} issues per batch
+3. Issues that are unrelated should be in separate batches (even single-issue batches)
+4. Be conservative - only batch issues that clearly belong together
+
+Respond with JSON only:
+{{
+ "batches": [
+ {{
+ "issue_numbers": [1, 2, 3],
+ "theme": "Authentication issues",
+ "reasoning": "All related to login flow",
+ "confidence": 0.85
+ }},
+ {{
+ "issue_numbers": [4],
+ "theme": "UI bug",
+ "reasoning": "Unrelated to other issues",
+ "confidence": 0.95
+ }}
+ ]
+}}"""
+
+ try:
+ ensure_claude_code_oauth_token()
+
+ logger.info(
+ f"[BATCH_ANALYZER] Analyzing {len(issues)} issues in single call"
+ )
+
+ # Using Sonnet for better analysis (still just 1 call)
+ client = ClaudeSDKClient(
+ options=ClaudeAgentOptions(
+ model="claude-sonnet-4-20250514",
+ system_prompt="You are an expert at analyzing GitHub issues and grouping related ones. Respond ONLY with valid JSON. Do NOT use any tools.",
+ allowed_tools=[],
+ max_turns=1,
+ cwd=str(self.project_dir.resolve()),
+ )
+ )
+
+ async with client:
+ await client.query(prompt)
+ response_text = await self._collect_response(client)
+
+ logger.info(
+ f"[BATCH_ANALYZER] Received response: {len(response_text)} chars"
+ )
+
+ # Parse JSON response
+ result = self._parse_json_response(response_text)
+
+ if "batches" in result:
+ return result["batches"]
+ else:
+ logger.warning(
+ "[BATCH_ANALYZER] No batches in response, using fallback"
+ )
+ return self._fallback_batches(issues)
+
+ except Exception as e:
+ logger.error(f"[BATCH_ANALYZER] Error: {e}")
+ import traceback
+
+ traceback.print_exc()
+ return self._fallback_batches(issues)
+
+ def _parse_json_response(self, response_text: str) -> dict[str, Any]:
+ """Parse JSON from Claude response, handling various formats."""
+ content = response_text.strip()
+
+ if not content:
+ raise ValueError("Empty response")
+
+ # Extract JSON from markdown code blocks if present
+ if "```json" in content:
+ content = content.split("```json")[1].split("```")[0].strip()
+ elif "```" in content:
+ content = content.split("```")[1].split("```")[0].strip()
+ else:
+ # Look for JSON object
+ if "{" in content:
+ start = content.find("{")
+ brace_count = 0
+ for i, char in enumerate(content[start:], start):
+ if char == "{":
+ brace_count += 1
+ elif char == "}":
+ brace_count -= 1
+ if brace_count == 0:
+ content = content[start : i + 1]
+ break
+
+ return json.loads(content)
+
+ def _fallback_batches(self, issues: list[dict[str, Any]]) -> list[dict[str, Any]]:
+ """Fallback: each issue is its own batch."""
+ return [
+ {
+ "issue_numbers": [issue["number"]],
+ "theme": issue.get("title", ""),
+ "reasoning": "Fallback: individual batch",
+ "confidence": 0.5,
+ }
+ for issue in issues
+ ]
+
+ async def _collect_response(self, client: Any) -> str:
+ """Collect text response from Claude client."""
+ response_text = ""
+
+ async for msg in client.receive_response():
+ msg_type = type(msg).__name__
+ if msg_type == "AssistantMessage" and hasattr(msg, "content"):
+ for block in msg.content:
+ if type(block).__name__ == "TextBlock" and hasattr(block, "text"):
+ response_text += block.text
+
+ return response_text
+
+
+# Keep old class for backwards compatibility but mark as deprecated
+class ClaudeSimilarityDetector(ClaudeBatchAnalyzer):
+ """DEPRECATED: Use ClaudeBatchAnalyzer instead."""
+
+ async def compare_issues(
+ self,
+ repo: str,
+ issue_a: dict[str, Any],
+ issue_b: dict[str, Any],
+ ) -> dict[str, Any]:
+ """DEPRECATED: Pairwise comparison. Use analyze_and_batch_issues instead."""
+ logger.warning("ClaudeSimilarityDetector.compare_issues is deprecated")
+ # Simple fallback for any code still using this
+ return {
+ "is_similar": False,
+ "overall_score": 0.0,
+ "reasoning": "DEPRECATED: Use ClaudeBatchAnalyzer.analyze_and_batch_issues",
+ }
+
+ async def precompute_embeddings(self, repo: str, issues: list[dict]) -> int:
+ """No-op for compatibility."""
+ return 0
+
+
+class BatchStatus(str, Enum):
+ """Status of an issue batch."""
+
+ PENDING = "pending"
+ ANALYZING = "analyzing"
+ CREATING_SPEC = "creating_spec"
+ BUILDING = "building"
+ QA_REVIEW = "qa_review"
+ PR_CREATED = "pr_created"
+ COMPLETED = "completed"
+ FAILED = "failed"
+
+
+@dataclass
+class IssueBatchItem:
+ """An issue within a batch."""
+
+ issue_number: int
+ title: str
+ body: str
+ labels: list[str] = field(default_factory=list)
+ similarity_to_primary: float = 1.0 # Primary issue has 1.0
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "issue_number": self.issue_number,
+ "title": self.title,
+ "body": self.body,
+ "labels": self.labels,
+ "similarity_to_primary": self.similarity_to_primary,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict[str, Any]) -> IssueBatchItem:
+ return cls(
+ issue_number=data["issue_number"],
+ title=data["title"],
+ body=data.get("body", ""),
+ labels=data.get("labels", []),
+ similarity_to_primary=data.get("similarity_to_primary", 1.0),
+ )
+
+
+@dataclass
+class IssueBatch:
+ """A batch of related issues to be fixed together."""
+
+ batch_id: str
+ repo: str
+ primary_issue: int # The "anchor" issue for the batch
+ issues: list[IssueBatchItem]
+ common_themes: list[str] = field(default_factory=list)
+ status: BatchStatus = BatchStatus.PENDING
+ spec_id: str | None = None
+ pr_number: int | None = None
+ error: str | None = None
+ created_at: str = field(
+ default_factory=lambda: datetime.now(timezone.utc).isoformat()
+ )
+ updated_at: str = field(
+ default_factory=lambda: datetime.now(timezone.utc).isoformat()
+ )
+ # AI validation results
+ validated: bool = False
+ validation_confidence: float = 0.0
+ validation_reasoning: str = ""
+ theme: str = "" # Refined theme from validation
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "batch_id": self.batch_id,
+ "repo": self.repo,
+ "primary_issue": self.primary_issue,
+ "issues": [i.to_dict() for i in self.issues],
+ "common_themes": self.common_themes,
+ "status": self.status.value,
+ "spec_id": self.spec_id,
+ "pr_number": self.pr_number,
+ "error": self.error,
+ "created_at": self.created_at,
+ "updated_at": self.updated_at,
+ "validated": self.validated,
+ "validation_confidence": self.validation_confidence,
+ "validation_reasoning": self.validation_reasoning,
+ "theme": self.theme,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict[str, Any]) -> IssueBatch:
+ return cls(
+ batch_id=data["batch_id"],
+ repo=data["repo"],
+ primary_issue=data["primary_issue"],
+ issues=[IssueBatchItem.from_dict(i) for i in data.get("issues", [])],
+ common_themes=data.get("common_themes", []),
+ status=BatchStatus(data.get("status", "pending")),
+ spec_id=data.get("spec_id"),
+ pr_number=data.get("pr_number"),
+ error=data.get("error"),
+ created_at=data.get("created_at", datetime.now(timezone.utc).isoformat()),
+ updated_at=data.get("updated_at", datetime.now(timezone.utc).isoformat()),
+ validated=data.get("validated", False),
+ validation_confidence=data.get("validation_confidence", 0.0),
+ validation_reasoning=data.get("validation_reasoning", ""),
+ theme=data.get("theme", ""),
+ )
+
+ async def save(self, github_dir: Path) -> None:
+ """Save batch to disk atomically with file locking."""
+ batches_dir = github_dir / "batches"
+ batches_dir.mkdir(parents=True, exist_ok=True)
+
+ # Update timestamp BEFORE serializing to dict
+ self.updated_at = datetime.now(timezone.utc).isoformat()
+
+ batch_file = batches_dir / f"batch_{self.batch_id}.json"
+ await locked_json_write(batch_file, self.to_dict(), timeout=5.0)
+
+ @classmethod
+ def load(cls, github_dir: Path, batch_id: str) -> IssueBatch | None:
+ """Load batch from disk."""
+ batch_file = github_dir / "batches" / f"batch_{batch_id}.json"
+ if not batch_file.exists():
+ return None
+
+ with open(batch_file) as f:
+ data = json.load(f)
+ return cls.from_dict(data)
+
+ def get_issue_numbers(self) -> list[int]:
+ """Get all issue numbers in the batch."""
+ return [issue.issue_number for issue in self.issues]
+
+ def update_status(self, status: BatchStatus, error: str | None = None) -> None:
+ """Update batch status."""
+ self.status = status
+ if error:
+ self.error = error
+ self.updated_at = datetime.now(timezone.utc).isoformat()
+
+
+class IssueBatcher:
+ """
+ Groups similar issues into batches for combined auto-fix.
+
+ Usage:
+ batcher = IssueBatcher(
+ github_dir=Path(".auto-claude/github"),
+ repo="owner/repo",
+ )
+
+ # Analyze and batch issues
+ batches = await batcher.create_batches(open_issues)
+
+ # Get batch for an issue
+ batch = batcher.get_batch_for_issue(123)
+ """
+
+ def __init__(
+ self,
+ github_dir: Path,
+ repo: str,
+ project_dir: Path | None = None,
+ similarity_threshold: float = SIMILAR_THRESHOLD,
+ min_batch_size: int = 1,
+ max_batch_size: int = 5,
+ api_key: str | None = None,
+ # AI validation settings
+ validate_batches: bool = True,
+ validation_model: str = "claude-sonnet-4-20250514",
+ validation_thinking_budget: int = 10000, # Medium thinking
+ ):
+ self.github_dir = github_dir
+ self.repo = repo
+ self.project_dir = (
+ project_dir or github_dir.parent.parent
+ ) # Default to project root
+ self.similarity_threshold = similarity_threshold
+ self.min_batch_size = min_batch_size
+ self.max_batch_size = max_batch_size
+ self.validate_batches_enabled = validate_batches
+
+ # Initialize Claude batch analyzer (replaces pairwise similarity detector)
+ self.analyzer = ClaudeBatchAnalyzer(project_dir=self.project_dir)
+
+ # Keep detector for backwards compatibility (deprecated)
+ self.detector = self.analyzer
+
+ # Initialize batch validator (uses Claude SDK with OAuth token)
+ self.validator = (
+ BatchValidator(
+ project_dir=self.project_dir,
+ model=validation_model,
+ thinking_budget=validation_thinking_budget,
+ )
+ if validate_batches
+ else None
+ )
+
+ # Cache for batches
+ self._batch_index: dict[int, str] = {} # issue_number -> batch_id
+ self._load_batch_index()
+
+ def _load_batch_index(self) -> None:
+ """Load batch index from disk."""
+ index_file = self.github_dir / "batches" / "index.json"
+ if index_file.exists():
+ with open(index_file) as f:
+ data = json.load(f)
+ self._batch_index = {
+ int(k): v for k, v in data.get("issue_to_batch", {}).items()
+ }
+
+ def _save_batch_index(self) -> None:
+ """Save batch index to disk."""
+ batches_dir = self.github_dir / "batches"
+ batches_dir.mkdir(parents=True, exist_ok=True)
+
+ index_file = batches_dir / "index.json"
+ with open(index_file, "w") as f:
+ json.dump(
+ {
+ "issue_to_batch": self._batch_index,
+ "updated_at": datetime.now(timezone.utc).isoformat(),
+ },
+ f,
+ indent=2,
+ )
+
+ def _generate_batch_id(self, primary_issue: int) -> str:
+ """Generate unique batch ID."""
+ timestamp = datetime.now(timezone.utc).strftime("%Y%m%d%H%M%S")
+ return f"{primary_issue}_{timestamp}"
+
+ def _pre_group_by_labels_and_keywords(
+ self,
+ issues: list[dict[str, Any]],
+ ) -> list[list[dict[str, Any]]]:
+ """
+ Fast O(n) pre-grouping by labels and title keywords.
+
+ This dramatically reduces the number of Claude API calls needed
+ by only comparing issues within the same pre-group.
+
+ Returns list of pre-groups (each group is a list of issues).
+ """
+ # Priority labels that strongly indicate grouping
+ grouping_labels = {
+ "bug",
+ "feature",
+ "enhancement",
+ "documentation",
+ "refactor",
+ "performance",
+ "security",
+ "ui",
+ "ux",
+ "frontend",
+ "backend",
+ "api",
+ "database",
+ "testing",
+ "infrastructure",
+ "ci/cd",
+ "high priority",
+ "low priority",
+ "critical",
+ "blocker",
+ }
+
+ # Group issues by their primary label
+ label_groups: dict[str, list[dict[str, Any]]] = {}
+ no_label_issues: list[dict[str, Any]] = []
+
+ for issue in issues:
+ labels = [
+ label.get("name", "").lower() for label in issue.get("labels", [])
+ ]
+
+ # Find the first grouping label
+ primary_label = None
+ for label in labels:
+ if label in grouping_labels:
+ primary_label = label
+ break
+
+ if primary_label:
+ if primary_label not in label_groups:
+ label_groups[primary_label] = []
+ label_groups[primary_label].append(issue)
+ else:
+ no_label_issues.append(issue)
+
+ # For issues without grouping labels, try keyword-based grouping
+ keyword_groups = self._group_by_title_keywords(no_label_issues)
+
+ # Combine all pre-groups
+ pre_groups = list(label_groups.values()) + keyword_groups
+
+ # Log pre-grouping results
+ total_issues = sum(len(g) for g in pre_groups)
+ logger.info(
+ f"Pre-grouped {total_issues} issues into {len(pre_groups)} groups "
+ f"(label groups: {len(label_groups)}, keyword groups: {len(keyword_groups)})"
+ )
+
+ return pre_groups
+
+ def _group_by_title_keywords(
+ self,
+ issues: list[dict[str, Any]],
+ ) -> list[list[dict[str, Any]]]:
+ """
+ Group issues by common keywords in their titles.
+
+ Returns list of groups.
+ """
+ if not issues:
+ return []
+
+ # Extract keywords from titles
+ keyword_map: dict[str, list[dict[str, Any]]] = {}
+ ungrouped: list[dict[str, Any]] = []
+
+ # Keywords that indicate related issues
+ grouping_keywords = {
+ "login",
+ "auth",
+ "authentication",
+ "oauth",
+ "session",
+ "api",
+ "endpoint",
+ "request",
+ "response",
+ "database",
+ "db",
+ "query",
+ "connection",
+ "ui",
+ "display",
+ "render",
+ "css",
+ "style",
+ "error",
+ "exception",
+ "crash",
+ "fail",
+ "performance",
+ "slow",
+ "memory",
+ "leak",
+ "test",
+ "coverage",
+ "mock",
+ "config",
+ "settings",
+ "env",
+ "build",
+ "deploy",
+ "ci",
+ }
+
+ for issue in issues:
+ title = issue.get("title", "").lower()
+
+ # Find matching keywords
+ matched_keyword = None
+ for keyword in grouping_keywords:
+ if keyword in title:
+ matched_keyword = keyword
+ break
+
+ if matched_keyword:
+ if matched_keyword not in keyword_map:
+ keyword_map[matched_keyword] = []
+ keyword_map[matched_keyword].append(issue)
+ else:
+ ungrouped.append(issue)
+
+ # Collect groups
+ groups = list(keyword_map.values())
+
+ # Add ungrouped issues as individual "groups" of 1
+ for issue in ungrouped:
+ groups.append([issue])
+
+ return groups
+
+ async def _analyze_issues_with_agents(
+ self,
+ issues: list[dict[str, Any]],
+ ) -> list[list[int]]:
+ """
+ Analyze issues using Claude agents to suggest batches.
+
+ Uses a two-phase approach:
+ 1. Fast O(n) pre-grouping by labels and keywords (no AI calls)
+ 2. One Claude call PER PRE-GROUP to analyze and suggest sub-batches
+
+ For 51 issues, this might result in ~5-10 Claude calls instead of 1275.
+
+ Returns list of clusters (each cluster is a list of issue numbers).
+ """
+ n = len(issues)
+
+ # Phase 1: Pre-group by labels and keywords (O(n), no AI calls)
+ pre_groups = self._pre_group_by_labels_and_keywords(issues)
+
+ # Calculate stats
+ total_api_calls_naive = n * (n - 1) // 2
+ total_api_calls_new = len([g for g in pre_groups if len(g) > 1])
+
+ logger.info(
+ f"Agent-based batching: {total_api_calls_new} Claude calls "
+ f"(was {total_api_calls_naive} with pairwise, saved {total_api_calls_naive - total_api_calls_new})"
+ )
+
+ # Phase 2: Use Claude agent to analyze each pre-group
+ all_batches: list[list[int]] = []
+
+ for group in pre_groups:
+ if len(group) == 1:
+ # Single issue = single batch, no AI needed
+ all_batches.append([group[0]["number"]])
+ continue
+
+ # Use Claude to analyze this group and suggest batches
+ logger.info(f"Analyzing pre-group of {len(group)} issues with Claude agent")
+
+ batch_suggestions = await self.analyzer.analyze_and_batch_issues(
+ issues=group,
+ max_batch_size=self.max_batch_size,
+ )
+
+ # Convert suggestions to clusters
+ for suggestion in batch_suggestions:
+ issue_numbers = suggestion.get("issue_numbers", [])
+ if issue_numbers:
+ all_batches.append(issue_numbers)
+ logger.info(
+ f" Batch: {issue_numbers} - {suggestion.get('theme', 'No theme')} "
+ f"(confidence: {suggestion.get('confidence', 0):.0%})"
+ )
+
+ logger.info(f"Created {len(all_batches)} batches from {n} issues")
+
+ return all_batches
+
+ async def _build_similarity_matrix(
+ self,
+ issues: list[dict[str, Any]],
+ ) -> tuple[dict[tuple[int, int], float], dict[int, dict[int, str]]]:
+ """
+ DEPRECATED: Use _analyze_issues_with_agents instead.
+
+ This method is kept for backwards compatibility but now uses
+ the agent-based approach internally.
+ """
+ # Use the new agent-based approach
+ clusters = await self._analyze_issues_with_agents(issues)
+
+ # Build a synthetic similarity matrix from the clusters
+ # (for backwards compatibility with _cluster_issues)
+ matrix = {}
+ reasoning = {}
+
+ for cluster in clusters:
+ # Issues in the same cluster are considered similar
+ for i, issue_a in enumerate(cluster):
+ if issue_a not in reasoning:
+ reasoning[issue_a] = {}
+ for issue_b in cluster[i + 1 :]:
+ if issue_b not in reasoning:
+ reasoning[issue_b] = {}
+ # Mark as similar (high score)
+ matrix[(issue_a, issue_b)] = 0.85
+ matrix[(issue_b, issue_a)] = 0.85
+ reasoning[issue_a][issue_b] = "Grouped by Claude agent analysis"
+ reasoning[issue_b][issue_a] = "Grouped by Claude agent analysis"
+
+ return matrix, reasoning
+
+ def _cluster_issues(
+ self,
+ issues: list[dict[str, Any]],
+ similarity_matrix: dict[tuple[int, int], float],
+ ) -> list[list[int]]:
+ """
+ Cluster issues using simple agglomerative approach.
+
+ Returns list of clusters, each cluster is a list of issue numbers.
+ """
+ issue_numbers = [i["number"] for i in issues]
+
+ # Start with each issue in its own cluster
+ clusters: list[set[int]] = [{n} for n in issue_numbers]
+
+ # Merge clusters that have similar issues
+ def cluster_similarity(c1: set[int], c2: set[int]) -> float:
+ """Average similarity between clusters."""
+ scores = []
+ for a in c1:
+ for b in c2:
+ if (a, b) in similarity_matrix:
+ scores.append(similarity_matrix[(a, b)])
+ return sum(scores) / len(scores) if scores else 0.0
+
+ # Iteratively merge most similar clusters
+ while len(clusters) > 1:
+ best_score = 0.0
+ best_pair = (-1, -1)
+
+ for i in range(len(clusters)):
+ for j in range(i + 1, len(clusters)):
+ score = cluster_similarity(clusters[i], clusters[j])
+ if score > best_score:
+ best_score = score
+ best_pair = (i, j)
+
+ # Stop if best similarity is below threshold
+ if best_score < self.similarity_threshold:
+ break
+
+ # Merge clusters
+ i, j = best_pair
+ merged = clusters[i] | clusters[j]
+
+ # Don't exceed max batch size
+ if len(merged) > self.max_batch_size:
+ break
+
+ clusters = [c for k, c in enumerate(clusters) if k not in (i, j)]
+ clusters.append(merged)
+
+ return [list(c) for c in clusters]
+
+ def _extract_common_themes(
+ self,
+ issues: list[dict[str, Any]],
+ ) -> list[str]:
+ """Extract common themes from issue titles and bodies."""
+ # Simple keyword extraction
+ all_text = " ".join(
+ f"{i.get('title', '')} {i.get('body', '')}" for i in issues
+ ).lower()
+
+ # Common tech keywords to look for
+ keywords = [
+ "authentication",
+ "login",
+ "oauth",
+ "session",
+ "api",
+ "endpoint",
+ "request",
+ "response",
+ "database",
+ "query",
+ "connection",
+ "timeout",
+ "error",
+ "exception",
+ "crash",
+ "bug",
+ "performance",
+ "slow",
+ "memory",
+ "leak",
+ "ui",
+ "display",
+ "render",
+ "style",
+ "test",
+ "coverage",
+ "assertion",
+ "mock",
+ ]
+
+ found = [kw for kw in keywords if kw in all_text]
+ return found[:5] # Limit to 5 themes
+
+ async def create_batches(
+ self,
+ issues: list[dict[str, Any]],
+ exclude_issue_numbers: set[int] | None = None,
+ ) -> list[IssueBatch]:
+ """
+ Create batches from a list of issues.
+
+ Args:
+ issues: List of issue dicts with number, title, body, labels
+ exclude_issue_numbers: Issues to exclude (already in batches)
+
+ Returns:
+ List of IssueBatch objects (validated if validation enabled)
+ """
+ exclude = exclude_issue_numbers or set()
+
+ # Filter to issues not already batched
+ available_issues = [
+ i
+ for i in issues
+ if i["number"] not in exclude and i["number"] not in self._batch_index
+ ]
+
+ if not available_issues:
+ logger.info("No new issues to batch")
+ return []
+
+ logger.info(f"Analyzing {len(available_issues)} issues for batching...")
+
+ # Build similarity matrix
+ similarity_matrix, _ = await self._build_similarity_matrix(available_issues)
+
+ # Cluster issues
+ clusters = self._cluster_issues(available_issues, similarity_matrix)
+
+ # Create initial batches from clusters
+ initial_batches = []
+ for cluster in clusters:
+ if len(cluster) < self.min_batch_size:
+ continue
+
+ # Find primary issue (most connected)
+ primary = max(
+ cluster,
+ key=lambda n: sum(
+ 1
+ for other in cluster
+ if n != other and (n, other) in similarity_matrix
+ ),
+ )
+
+ # Build batch items
+ cluster_issues = [i for i in available_issues if i["number"] in cluster]
+ items = []
+ for issue in cluster_issues:
+ similarity = (
+ 1.0
+ if issue["number"] == primary
+ else similarity_matrix.get((primary, issue["number"]), 0.0)
+ )
+
+ items.append(
+ IssueBatchItem(
+ issue_number=issue["number"],
+ title=issue.get("title", ""),
+ body=issue.get("body", ""),
+ labels=[
+ label.get("name", "") for label in issue.get("labels", [])
+ ],
+ similarity_to_primary=similarity,
+ )
+ )
+
+ # Sort by similarity (primary first)
+ items.sort(key=lambda x: x.similarity_to_primary, reverse=True)
+
+ # Extract themes
+ themes = self._extract_common_themes(cluster_issues)
+
+ # Create batch
+ batch = IssueBatch(
+ batch_id=self._generate_batch_id(primary),
+ repo=self.repo,
+ primary_issue=primary,
+ issues=items,
+ common_themes=themes,
+ )
+ initial_batches.append((batch, cluster_issues))
+
+ # Validate batches with AI if enabled
+ validated_batches = []
+ if self.validate_batches_enabled and self.validator:
+ logger.info(f"Validating {len(initial_batches)} batches with AI...")
+ validated_batches = await self._validate_and_split_batches(
+ initial_batches, available_issues, similarity_matrix
+ )
+ else:
+ # No validation - use batches as-is
+ for batch, _ in initial_batches:
+ batch.validated = True
+ batch.validation_confidence = 1.0
+ batch.validation_reasoning = "Validation disabled"
+ batch.theme = batch.common_themes[0] if batch.common_themes else ""
+ validated_batches.append(batch)
+
+ # Save validated batches
+ final_batches = []
+ for batch in validated_batches:
+ # Update index
+ for item in batch.issues:
+ self._batch_index[item.issue_number] = batch.batch_id
+
+ # Save batch
+ batch.save(self.github_dir)
+ final_batches.append(batch)
+
+ logger.info(
+ f"Saved batch {batch.batch_id} with {len(batch.issues)} issues: "
+ f"{[i.issue_number for i in batch.issues]} "
+ f"(validated={batch.validated}, confidence={batch.validation_confidence:.0%})"
+ )
+
+ # Save index
+ self._save_batch_index()
+
+ return final_batches
+
+ async def _validate_and_split_batches(
+ self,
+ initial_batches: list[tuple[IssueBatch, list[dict[str, Any]]]],
+ all_issues: list[dict[str, Any]],
+ similarity_matrix: dict[tuple[int, int], float],
+ ) -> list[IssueBatch]:
+ """
+ Validate batches with AI and split invalid ones.
+
+ Returns list of validated batches (may be more than input if splits occur).
+ """
+ validated = []
+
+ for batch, cluster_issues in initial_batches:
+ # Prepare issues for validation
+ issues_for_validation = [
+ {
+ "issue_number": item.issue_number,
+ "title": item.title,
+ "body": item.body,
+ "labels": item.labels,
+ "similarity_to_primary": item.similarity_to_primary,
+ }
+ for item in batch.issues
+ ]
+
+ # Validate with AI
+ result = await self.validator.validate_batch(
+ batch_id=batch.batch_id,
+ primary_issue=batch.primary_issue,
+ issues=issues_for_validation,
+ themes=batch.common_themes,
+ )
+
+ if result.is_valid:
+ # Batch is valid - update with validation results
+ batch.validated = True
+ batch.validation_confidence = result.confidence
+ batch.validation_reasoning = result.reasoning
+ batch.theme = result.common_theme or (
+ batch.common_themes[0] if batch.common_themes else ""
+ )
+ validated.append(batch)
+ logger.info(f"Batch {batch.batch_id} validated: {result.reasoning}")
+ else:
+ # Batch is invalid - need to split
+ logger.info(
+ f"Batch {batch.batch_id} invalid ({result.reasoning}), splitting..."
+ )
+
+ if result.suggested_splits:
+ # Use AI's suggested splits
+ for split_issues in result.suggested_splits:
+ if len(split_issues) < self.min_batch_size:
+ continue
+
+ # Create new batch from split
+ split_batch = self._create_batch_from_issues(
+ issue_numbers=split_issues,
+ all_issues=cluster_issues,
+ similarity_matrix=similarity_matrix,
+ )
+ if split_batch:
+ split_batch.validated = True
+ split_batch.validation_confidence = result.confidence
+ split_batch.validation_reasoning = (
+ f"Split from {batch.batch_id}: {result.reasoning}"
+ )
+ split_batch.theme = result.common_theme or ""
+ validated.append(split_batch)
+ else:
+ # No suggested splits - treat each issue as individual batch
+ for item in batch.issues:
+ single_batch = IssueBatch(
+ batch_id=self._generate_batch_id(item.issue_number),
+ repo=self.repo,
+ primary_issue=item.issue_number,
+ issues=[item],
+ common_themes=[],
+ validated=True,
+ validation_confidence=result.confidence,
+ validation_reasoning=f"Split from invalid batch: {result.reasoning}",
+ theme="",
+ )
+ validated.append(single_batch)
+
+ return validated
+
+ def _create_batch_from_issues(
+ self,
+ issue_numbers: list[int],
+ all_issues: list[dict[str, Any]],
+ similarity_matrix: dict[tuple[int, int], float],
+ ) -> IssueBatch | None:
+ """Create a batch from a subset of issues."""
+ # Find issues matching the numbers
+ batch_issues = [i for i in all_issues if i["number"] in issue_numbers]
+ if not batch_issues:
+ return None
+
+ # Find primary (most connected within this subset)
+ primary = max(
+ issue_numbers,
+ key=lambda n: sum(
+ 1
+ for other in issue_numbers
+ if n != other and (n, other) in similarity_matrix
+ ),
+ )
+
+ # Build items
+ items = []
+ for issue in batch_issues:
+ similarity = (
+ 1.0
+ if issue["number"] == primary
+ else similarity_matrix.get((primary, issue["number"]), 0.0)
+ )
+
+ items.append(
+ IssueBatchItem(
+ issue_number=issue["number"],
+ title=issue.get("title", ""),
+ body=issue.get("body", ""),
+ labels=[label.get("name", "") for label in issue.get("labels", [])],
+ similarity_to_primary=similarity,
+ )
+ )
+
+ items.sort(key=lambda x: x.similarity_to_primary, reverse=True)
+ themes = self._extract_common_themes(batch_issues)
+
+ return IssueBatch(
+ batch_id=self._generate_batch_id(primary),
+ repo=self.repo,
+ primary_issue=primary,
+ issues=items,
+ common_themes=themes,
+ )
+
+ def get_batch_for_issue(self, issue_number: int) -> IssueBatch | None:
+ """Get the batch containing an issue."""
+ batch_id = self._batch_index.get(issue_number)
+ if not batch_id:
+ return None
+ return IssueBatch.load(self.github_dir, batch_id)
+
+ def get_all_batches(self) -> list[IssueBatch]:
+ """Get all batches."""
+ batches_dir = self.github_dir / "batches"
+ if not batches_dir.exists():
+ return []
+
+ batches = []
+ for batch_file in batches_dir.glob("batch_*.json"):
+ try:
+ with open(batch_file) as f:
+ data = json.load(f)
+ batches.append(IssueBatch.from_dict(data))
+ except Exception as e:
+ logger.error(f"Error loading batch {batch_file}: {e}")
+
+ return sorted(batches, key=lambda b: b.created_at, reverse=True)
+
+ def get_pending_batches(self) -> list[IssueBatch]:
+ """Get batches that need processing."""
+ return [
+ b
+ for b in self.get_all_batches()
+ if b.status in (BatchStatus.PENDING, BatchStatus.ANALYZING)
+ ]
+
+ def get_active_batches(self) -> list[IssueBatch]:
+ """Get batches currently being processed."""
+ return [
+ b
+ for b in self.get_all_batches()
+ if b.status
+ in (
+ BatchStatus.CREATING_SPEC,
+ BatchStatus.BUILDING,
+ BatchStatus.QA_REVIEW,
+ )
+ ]
+
+ def is_issue_in_batch(self, issue_number: int) -> bool:
+ """Check if an issue is already in a batch."""
+ return issue_number in self._batch_index
+
+ def remove_batch(self, batch_id: str) -> bool:
+ """Remove a batch and update index."""
+ batch = IssueBatch.load(self.github_dir, batch_id)
+ if not batch:
+ return False
+
+ # Remove from index
+ for issue_num in batch.get_issue_numbers():
+ self._batch_index.pop(issue_num, None)
+ self._save_batch_index()
+
+ # Delete batch file
+ batch_file = self.github_dir / "batches" / f"batch_{batch_id}.json"
+ if batch_file.exists():
+ batch_file.unlink()
+
+ return True
diff --git a/apps/backend/runners/github/batch_validator.py b/apps/backend/runners/github/batch_validator.py
new file mode 100644
index 00000000..87625341
--- /dev/null
+++ b/apps/backend/runners/github/batch_validator.py
@@ -0,0 +1,332 @@
+"""
+Batch Validation Agent
+======================
+
+AI layer that validates issue batching using Claude SDK with extended thinking.
+Reviews whether semantically grouped issues actually belong together.
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any
+
+logger = logging.getLogger(__name__)
+
+# Check for Claude SDK availability
+try:
+ from claude_agent_sdk import ClaudeAgentOptions, ClaudeSDKClient
+
+ CLAUDE_SDK_AVAILABLE = True
+except (ImportError, ValueError, SystemError):
+ CLAUDE_SDK_AVAILABLE = False
+
+# Default model and thinking configuration
+DEFAULT_MODEL = "claude-sonnet-4-20250514"
+DEFAULT_THINKING_BUDGET = 10000 # Medium thinking
+
+
+@dataclass
+class BatchValidationResult:
+ """Result of batch validation."""
+
+ batch_id: str
+ is_valid: bool
+ confidence: float # 0.0 - 1.0
+ reasoning: str
+ suggested_splits: list[list[int]] | None # If invalid, suggest how to split
+ common_theme: str # Refined theme description
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "batch_id": self.batch_id,
+ "is_valid": self.is_valid,
+ "confidence": self.confidence,
+ "reasoning": self.reasoning,
+ "suggested_splits": self.suggested_splits,
+ "common_theme": self.common_theme,
+ }
+
+
+VALIDATION_PROMPT = """You are reviewing a batch of GitHub issues that were grouped together by semantic similarity.
+Your job is to validate whether these issues truly belong together for a SINGLE combined fix/PR.
+
+Issues should be batched together ONLY if:
+1. They describe the SAME root cause or closely related symptoms
+2. They can realistically be fixed together in ONE pull request
+3. Fixing one would naturally address the others
+4. They affect the same component/area of the codebase
+
+Issues should NOT be batched together if:
+1. They are merely topically similar but have different root causes
+2. They require separate, unrelated fixes
+3. One is a feature request and another is a bug fix
+4. They affect completely different parts of the codebase
+
+## Batch to Validate
+
+Batch ID: {batch_id}
+Primary Issue: #{primary_issue}
+Detected Themes: {themes}
+
+### Issues in this batch:
+
+{issues_formatted}
+
+## Your Task
+
+Analyze whether these issues truly belong together. Consider:
+- Do they share a common root cause?
+- Could a single PR reasonably fix all of them?
+- Are there any outliers that don't fit?
+
+Respond with a JSON object:
+```json
+{{
+ "is_valid": true/false,
+ "confidence": 0.0-1.0,
+ "reasoning": "Brief explanation of your decision",
+ "suggested_splits": null or [[issue_numbers], [issue_numbers]] if invalid,
+ "common_theme": "Refined description of what ties valid issues together"
+}}
+```
+
+Only output the JSON, no other text."""
+
+
+class BatchValidator:
+ """
+ Validates issue batches using Claude SDK with extended thinking.
+
+ Usage:
+ validator = BatchValidator(project_dir=Path("."))
+ result = await validator.validate_batch(batch)
+
+ if not result.is_valid:
+ # Split the batch according to suggestions
+ new_batches = result.suggested_splits
+ """
+
+ def __init__(
+ self,
+ project_dir: Path | None = None,
+ model: str = DEFAULT_MODEL,
+ thinking_budget: int = DEFAULT_THINKING_BUDGET,
+ ):
+ self.model = model
+ self.thinking_budget = thinking_budget
+ self.project_dir = project_dir or Path.cwd()
+
+ if not CLAUDE_SDK_AVAILABLE:
+ logger.warning(
+ "claude-agent-sdk not available. Batch validation will be skipped."
+ )
+
+ def _format_issues(self, issues: list[dict[str, Any]]) -> str:
+ """Format issues for the prompt."""
+ formatted = []
+ for issue in issues:
+ labels = ", ".join(issue.get("labels", [])) or "none"
+ body = issue.get("body", "")[:500] # Truncate long bodies
+ if len(issue.get("body", "")) > 500:
+ body += "..."
+
+ formatted.append(f"""
+**Issue #{issue["issue_number"]}**: {issue["title"]}
+- Labels: {labels}
+- Similarity to primary: {issue.get("similarity_to_primary", 1.0):.0%}
+- Body: {body}
+""")
+ return "\n---\n".join(formatted)
+
+ async def validate_batch(
+ self,
+ batch_id: str,
+ primary_issue: int,
+ issues: list[dict[str, Any]],
+ themes: list[str],
+ ) -> BatchValidationResult:
+ """
+ Validate a batch of issues.
+
+ Args:
+ batch_id: Unique batch identifier
+ primary_issue: The primary/anchor issue number
+ issues: List of issue dicts with issue_number, title, body, labels, similarity_to_primary
+ themes: Detected common themes
+
+ Returns:
+ BatchValidationResult with validation decision
+ """
+ # Single issue batches are always valid
+ if len(issues) <= 1:
+ return BatchValidationResult(
+ batch_id=batch_id,
+ is_valid=True,
+ confidence=1.0,
+ reasoning="Single issue batch - no validation needed",
+ suggested_splits=None,
+ common_theme=themes[0] if themes else "single issue",
+ )
+
+ # Check if SDK is available
+ if not CLAUDE_SDK_AVAILABLE:
+ logger.warning("Claude SDK not available, assuming batch is valid")
+ return BatchValidationResult(
+ batch_id=batch_id,
+ is_valid=True,
+ confidence=0.5,
+ reasoning="Validation skipped - Claude SDK not available",
+ suggested_splits=None,
+ common_theme=themes[0] if themes else "",
+ )
+
+ # Format the prompt
+ prompt = VALIDATION_PROMPT.format(
+ batch_id=batch_id,
+ primary_issue=primary_issue,
+ themes=", ".join(themes) if themes else "none detected",
+ issues_formatted=self._format_issues(issues),
+ )
+
+ try:
+ # Create settings for minimal permissions (no tools needed)
+ settings = {
+ "permissions": {
+ "defaultMode": "ignore",
+ "allow": [],
+ },
+ }
+
+ settings_file = self.project_dir / ".batch_validator_settings.json"
+ with open(settings_file, "w") as f:
+ json.dump(settings, f)
+
+ try:
+ # Create Claude SDK client with extended thinking
+ client = ClaudeSDKClient(
+ options=ClaudeAgentOptions(
+ model=self.model,
+ system_prompt="You are an expert at analyzing GitHub issues and determining if they should be grouped together for a combined fix.",
+ allowed_tools=[], # No tools needed for this analysis
+ max_turns=1,
+ cwd=str(self.project_dir.resolve()),
+ settings=str(settings_file.resolve()),
+ max_thinking_tokens=self.thinking_budget, # Extended thinking
+ )
+ )
+
+ async with client:
+ await client.query(prompt)
+ result_text = await self._collect_response(client)
+
+ # Parse JSON response
+ result_json = self._parse_json_response(result_text)
+
+ return BatchValidationResult(
+ batch_id=batch_id,
+ is_valid=result_json.get("is_valid", True),
+ confidence=result_json.get("confidence", 0.5),
+ reasoning=result_json.get("reasoning", "No reasoning provided"),
+ suggested_splits=result_json.get("suggested_splits"),
+ common_theme=result_json.get("common_theme", ""),
+ )
+
+ finally:
+ # Cleanup settings file
+ if settings_file.exists():
+ settings_file.unlink()
+
+ except Exception as e:
+ logger.error(f"Batch validation failed: {e}")
+ # On error, assume valid to not block the flow
+ return BatchValidationResult(
+ batch_id=batch_id,
+ is_valid=True,
+ confidence=0.5,
+ reasoning=f"Validation error (assuming valid): {str(e)}",
+ suggested_splits=None,
+ common_theme=themes[0] if themes else "",
+ )
+
+ async def _collect_response(self, client: Any) -> str:
+ """Collect text response from Claude client."""
+ response_text = ""
+
+ async for msg in client.receive_response():
+ msg_type = type(msg).__name__
+
+ if msg_type == "AssistantMessage":
+ for content in msg.content:
+ if hasattr(content, "text"):
+ response_text += content.text
+
+ return response_text
+
+ def _parse_json_response(self, text: str) -> dict[str, Any]:
+ """Parse JSON from the response, handling markdown code blocks."""
+ # Try to extract JSON from markdown code block
+ if "```json" in text:
+ start = text.find("```json") + 7
+ end = text.find("```", start)
+ if end > start:
+ text = text[start:end].strip()
+ elif "```" in text:
+ start = text.find("```") + 3
+ end = text.find("```", start)
+ if end > start:
+ text = text[start:end].strip()
+
+ try:
+ return json.loads(text)
+ except json.JSONDecodeError:
+ # Try to find JSON object in text
+ start = text.find("{")
+ end = text.rfind("}") + 1
+ if start >= 0 and end > start:
+ return json.loads(text[start:end])
+ raise
+
+
+async def validate_batches(
+ batches: list[dict[str, Any]],
+ project_dir: Path | None = None,
+ model: str = DEFAULT_MODEL,
+ thinking_budget: int = DEFAULT_THINKING_BUDGET,
+) -> list[BatchValidationResult]:
+ """
+ Validate multiple batches.
+
+ Args:
+ batches: List of batch dicts with batch_id, primary_issue, issues, common_themes
+ project_dir: Project directory for Claude SDK
+ model: Model to use for validation
+ thinking_budget: Token budget for extended thinking
+
+ Returns:
+ List of BatchValidationResult
+ """
+ validator = BatchValidator(
+ project_dir=project_dir,
+ model=model,
+ thinking_budget=thinking_budget,
+ )
+ results = []
+
+ for batch in batches:
+ result = await validator.validate_batch(
+ batch_id=batch["batch_id"],
+ primary_issue=batch["primary_issue"],
+ issues=batch["issues"],
+ themes=batch.get("common_themes", []),
+ )
+ results.append(result)
+ logger.info(
+ f"Batch {batch['batch_id']}: valid={result.is_valid}, "
+ f"confidence={result.confidence:.0%}, theme='{result.common_theme}'"
+ )
+
+ return results
diff --git a/apps/backend/runners/github/bot_detection.py b/apps/backend/runners/github/bot_detection.py
new file mode 100644
index 00000000..6821ab4c
--- /dev/null
+++ b/apps/backend/runners/github/bot_detection.py
@@ -0,0 +1,405 @@
+"""
+Bot Detection for GitHub Automation
+====================================
+
+Prevents infinite loops by detecting when the bot is reviewing its own work.
+
+Key Features:
+- Identifies bot user from configured token
+- Skips PRs authored by the bot
+- Skips re-reviewing bot commits
+- Implements "cooling off" period to prevent rapid re-reviews
+- Tracks reviewed commits to avoid duplicate reviews
+
+Usage:
+ detector = BotDetector(bot_token="ghp_...")
+
+ # Check if PR should be skipped
+ should_skip, reason = detector.should_skip_pr_review(pr_data, commits)
+ if should_skip:
+ print(f"Skipping PR: {reason}")
+ return
+
+ # After successful review, mark as reviewed
+ detector.mark_reviewed(pr_number, head_sha)
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import subprocess
+import sys
+from dataclasses import dataclass, field
+from datetime import datetime, timedelta
+from pathlib import Path
+
+
+@dataclass
+class BotDetectionState:
+ """State for tracking reviewed PRs and commits."""
+
+ # PR number -> set of reviewed commit SHAs
+ reviewed_commits: dict[int, list[str]] = field(default_factory=dict)
+
+ # PR number -> last review timestamp (ISO format)
+ last_review_times: dict[int, str] = field(default_factory=dict)
+
+ def to_dict(self) -> dict:
+ """Convert to dictionary for JSON serialization."""
+ return {
+ "reviewed_commits": self.reviewed_commits,
+ "last_review_times": self.last_review_times,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict) -> BotDetectionState:
+ """Load from dictionary."""
+ return cls(
+ reviewed_commits=data.get("reviewed_commits", {}),
+ last_review_times=data.get("last_review_times", {}),
+ )
+
+ def save(self, state_dir: Path) -> None:
+ """Save state to disk."""
+ state_dir.mkdir(parents=True, exist_ok=True)
+ state_file = state_dir / "bot_detection_state.json"
+
+ with open(state_file, "w") as f:
+ json.dump(self.to_dict(), f, indent=2)
+
+ @classmethod
+ def load(cls, state_dir: Path) -> BotDetectionState:
+ """Load state from disk."""
+ state_file = state_dir / "bot_detection_state.json"
+
+ if not state_file.exists():
+ return cls()
+
+ with open(state_file) as f:
+ return cls.from_dict(json.load(f))
+
+
+class BotDetector:
+ """
+ Detects bot-authored PRs and commits to prevent infinite review loops.
+
+ Configuration via GitHubRunnerConfig:
+ - review_own_prs: bool = False (whether bot can review its own PRs)
+ - bot_token: str | None (separate bot account token)
+
+ Automatic safeguards:
+ - 1-minute cooling off period between reviews of same PR (for testing)
+ - Tracks reviewed commit SHAs to avoid duplicate reviews
+ - Identifies bot user from token to skip bot-authored content
+ """
+
+ # Cooling off period in minutes (reduced to 1 for testing large PRs)
+ COOLING_OFF_MINUTES = 1
+
+ def __init__(
+ self,
+ state_dir: Path,
+ bot_token: str | None = None,
+ review_own_prs: bool = False,
+ ):
+ """
+ Initialize bot detector.
+
+ Args:
+ state_dir: Directory for storing detection state
+ bot_token: GitHub token for bot (to identify bot user)
+ review_own_prs: Whether to allow reviewing bot's own PRs
+ """
+ self.state_dir = state_dir
+ self.bot_token = bot_token
+ self.review_own_prs = review_own_prs
+
+ # Load or initialize state
+ self.state = BotDetectionState.load(state_dir)
+
+ # Identify bot username from token
+ self.bot_username = self._get_bot_username()
+
+ print(
+ f"[BotDetector] Initialized: bot_user={self.bot_username}, review_own_prs={review_own_prs}",
+ file=sys.stderr,
+ )
+
+ def _get_bot_username(self) -> str | None:
+ """
+ Get the bot's GitHub username from the token.
+
+ Returns:
+ Bot username or None if token not provided or invalid
+ """
+ if not self.bot_token:
+ print(
+ "[BotDetector] No bot token provided, cannot identify bot user",
+ file=sys.stderr,
+ )
+ return None
+
+ try:
+ # Use gh api to get authenticated user
+ # Pass token via environment variable to avoid exposing it in process listings
+ env = os.environ.copy()
+ env["GH_TOKEN"] = self.bot_token
+ result = subprocess.run(
+ [
+ "gh",
+ "api",
+ "user",
+ ],
+ capture_output=True,
+ text=True,
+ timeout=5,
+ env=env,
+ )
+
+ if result.returncode == 0:
+ user_data = json.loads(result.stdout)
+ username = user_data.get("login")
+ print(f"[BotDetector] Identified bot user: {username}")
+ return username
+ else:
+ print(f"[BotDetector] Failed to identify bot user: {result.stderr}")
+ return None
+
+ except Exception as e:
+ print(f"[BotDetector] Error identifying bot user: {e}")
+ return None
+
+ def is_bot_pr(self, pr_data: dict) -> bool:
+ """
+ Check if PR was created by the bot.
+
+ Args:
+ pr_data: PR data from GitHub API (must have 'author' field)
+
+ Returns:
+ True if PR author matches bot username
+ """
+ if not self.bot_username:
+ return False
+
+ pr_author = pr_data.get("author", {}).get("login")
+ is_bot = pr_author == self.bot_username
+
+ if is_bot:
+ print(f"[BotDetector] PR is bot-authored: {pr_author}")
+
+ return is_bot
+
+ def is_bot_commit(self, commit_data: dict) -> bool:
+ """
+ Check if commit was authored by the bot.
+
+ Args:
+ commit_data: Commit data from GitHub API (must have 'author' field)
+
+ Returns:
+ True if commit author matches bot username
+ """
+ if not self.bot_username:
+ return False
+
+ # Check both author and committer (could be different)
+ commit_author = commit_data.get("author", {}).get("login")
+ commit_committer = commit_data.get("committer", {}).get("login")
+
+ is_bot = (
+ commit_author == self.bot_username or commit_committer == self.bot_username
+ )
+
+ if is_bot:
+ print(
+ f"[BotDetector] Commit is bot-authored: {commit_author or commit_committer}"
+ )
+
+ return is_bot
+
+ def get_last_commit_sha(self, commits: list[dict]) -> str | None:
+ """
+ Get the SHA of the most recent commit.
+
+ Args:
+ commits: List of commit data from GitHub API
+
+ Returns:
+ SHA of latest commit or None if no commits
+ """
+ if not commits:
+ return None
+
+ # GitHub API returns commits in chronological order (oldest first, newest last)
+ latest = commits[-1]
+ return latest.get("oid") or latest.get("sha")
+
+ def is_within_cooling_off(self, pr_number: int) -> tuple[bool, str]:
+ """
+ Check if PR is within cooling off period.
+
+ Args:
+ pr_number: The PR number
+
+ Returns:
+ Tuple of (is_cooling_off, reason_message)
+ """
+ last_review_str = self.state.last_review_times.get(str(pr_number))
+
+ if not last_review_str:
+ return False, ""
+
+ try:
+ last_review = datetime.fromisoformat(last_review_str)
+ time_since = datetime.now() - last_review
+
+ if time_since < timedelta(minutes=self.COOLING_OFF_MINUTES):
+ minutes_left = self.COOLING_OFF_MINUTES - (
+ time_since.total_seconds() / 60
+ )
+ reason = (
+ f"Cooling off period active (reviewed {int(time_since.total_seconds() / 60)}m ago, "
+ f"{int(minutes_left)}m remaining)"
+ )
+ print(f"[BotDetector] PR #{pr_number}: {reason}")
+ return True, reason
+
+ except (ValueError, TypeError) as e:
+ print(f"[BotDetector] Error parsing last review time: {e}")
+
+ return False, ""
+
+ def has_reviewed_commit(self, pr_number: int, commit_sha: str) -> bool:
+ """
+ Check if we've already reviewed this specific commit.
+
+ Args:
+ pr_number: The PR number
+ commit_sha: The commit SHA to check
+
+ Returns:
+ True if this commit was already reviewed
+ """
+ reviewed = self.state.reviewed_commits.get(str(pr_number), [])
+ return commit_sha in reviewed
+
+ def should_skip_pr_review(
+ self,
+ pr_number: int,
+ pr_data: dict,
+ commits: list[dict] | None = None,
+ ) -> tuple[bool, str]:
+ """
+ Determine if we should skip reviewing this PR.
+
+ This is the main entry point for bot detection logic.
+
+ Args:
+ pr_number: The PR number
+ pr_data: PR data from GitHub API
+ commits: Optional list of commits in the PR
+
+ Returns:
+ Tuple of (should_skip, reason)
+ """
+ # Check 1: Is this a bot-authored PR?
+ if not self.review_own_prs and self.is_bot_pr(pr_data):
+ reason = f"PR authored by bot user ({self.bot_username})"
+ print(f"[BotDetector] SKIP PR #{pr_number}: {reason}")
+ return True, reason
+
+ # Check 2: Is the latest commit by the bot?
+ if commits and not self.review_own_prs:
+ latest_commit = commits[0] if commits else None
+ if latest_commit and self.is_bot_commit(latest_commit):
+ reason = "Latest commit authored by bot (likely an auto-fix)"
+ print(f"[BotDetector] SKIP PR #{pr_number}: {reason}")
+ return True, reason
+
+ # Check 3: Are we in the cooling off period?
+ is_cooling, reason = self.is_within_cooling_off(pr_number)
+ if is_cooling:
+ print(f"[BotDetector] SKIP PR #{pr_number}: {reason}")
+ return True, reason
+
+ # Check 4: Have we already reviewed this exact commit?
+ head_sha = self.get_last_commit_sha(commits) if commits else None
+ if head_sha and self.has_reviewed_commit(pr_number, head_sha):
+ reason = f"Already reviewed commit {head_sha[:8]}"
+ print(f"[BotDetector] SKIP PR #{pr_number}: {reason}")
+ return True, reason
+
+ # All checks passed - safe to review
+ print(f"[BotDetector] PR #{pr_number} is safe to review")
+ return False, ""
+
+ def mark_reviewed(self, pr_number: int, commit_sha: str) -> None:
+ """
+ Mark a PR as reviewed at a specific commit.
+
+ This should be called after successfully posting a review.
+
+ Args:
+ pr_number: The PR number
+ commit_sha: The commit SHA that was reviewed
+ """
+ pr_key = str(pr_number)
+
+ # Add to reviewed commits
+ if pr_key not in self.state.reviewed_commits:
+ self.state.reviewed_commits[pr_key] = []
+
+ if commit_sha not in self.state.reviewed_commits[pr_key]:
+ self.state.reviewed_commits[pr_key].append(commit_sha)
+
+ # Update last review time
+ self.state.last_review_times[pr_key] = datetime.now().isoformat()
+
+ # Save state
+ self.state.save(self.state_dir)
+
+ print(
+ f"[BotDetector] Marked PR #{pr_number} as reviewed at {commit_sha[:8]} "
+ f"({len(self.state.reviewed_commits[pr_key])} total commits reviewed)"
+ )
+
+ def clear_pr_state(self, pr_number: int) -> None:
+ """
+ Clear tracking state for a PR (e.g., when PR is closed/merged).
+
+ Args:
+ pr_number: The PR number
+ """
+ pr_key = str(pr_number)
+
+ if pr_key in self.state.reviewed_commits:
+ del self.state.reviewed_commits[pr_key]
+
+ if pr_key in self.state.last_review_times:
+ del self.state.last_review_times[pr_key]
+
+ self.state.save(self.state_dir)
+
+ print(f"[BotDetector] Cleared state for PR #{pr_number}")
+
+ def get_stats(self) -> dict:
+ """
+ Get statistics about bot detection activity.
+
+ Returns:
+ Dictionary with stats
+ """
+ total_prs = len(self.state.reviewed_commits)
+ total_reviews = sum(
+ len(commits) for commits in self.state.reviewed_commits.values()
+ )
+
+ return {
+ "bot_username": self.bot_username,
+ "review_own_prs": self.review_own_prs,
+ "total_prs_tracked": total_prs,
+ "total_reviews_performed": total_reviews,
+ "cooling_off_minutes": self.COOLING_OFF_MINUTES,
+ }
diff --git a/apps/backend/runners/github/bot_detection_example.py b/apps/backend/runners/github/bot_detection_example.py
new file mode 100644
index 00000000..9b14eeca
--- /dev/null
+++ b/apps/backend/runners/github/bot_detection_example.py
@@ -0,0 +1,154 @@
+"""
+Bot Detection Integration Example
+==================================
+
+Demonstrates how to use the bot detection system to prevent infinite loops.
+"""
+
+from pathlib import Path
+
+from models import GitHubRunnerConfig
+from orchestrator import GitHubOrchestrator
+
+
+async def example_with_bot_detection():
+ """Example: Reviewing PRs with bot detection enabled."""
+
+ # Create config with bot detection
+ config = GitHubRunnerConfig(
+ token="ghp_user_token",
+ repo="owner/repo",
+ bot_token="ghp_bot_token", # Bot's token for self-identification
+ pr_review_enabled=True,
+ auto_post_reviews=False, # Manual review posting for this example
+ review_own_prs=False, # CRITICAL: Prevent reviewing own PRs
+ )
+
+ # Initialize orchestrator (bot detector is auto-initialized)
+ orchestrator = GitHubOrchestrator(
+ project_dir=Path("/path/to/project"),
+ config=config,
+ )
+
+ print(f"Bot username: {orchestrator.bot_detector.bot_username}")
+ print(f"Review own PRs: {orchestrator.bot_detector.review_own_prs}")
+ print(
+ f"Cooling off period: {orchestrator.bot_detector.COOLING_OFF_MINUTES} minutes"
+ )
+ print()
+
+ # Scenario 1: Review a human-authored PR
+ print("=== Scenario 1: Human PR ===")
+ result = await orchestrator.review_pr(pr_number=123)
+ print(f"Result: {result.summary}")
+ print(f"Findings: {len(result.findings)}")
+ print()
+
+ # Scenario 2: Try to review immediately again (cooling off)
+ print("=== Scenario 2: Immediate re-review (should skip) ===")
+ result = await orchestrator.review_pr(pr_number=123)
+ print(f"Result: {result.summary}")
+ print()
+
+ # Scenario 3: Review bot-authored PR (should skip)
+ print("=== Scenario 3: Bot-authored PR (should skip) ===")
+ result = await orchestrator.review_pr(pr_number=456) # Assume this is bot's PR
+ print(f"Result: {result.summary}")
+ print()
+
+ # Check statistics
+ stats = orchestrator.bot_detector.get_stats()
+ print("=== Bot Detection Statistics ===")
+ print(f"Bot username: {stats['bot_username']}")
+ print(f"Total PRs tracked: {stats['total_prs_tracked']}")
+ print(f"Total reviews: {stats['total_reviews_performed']}")
+
+
+async def example_manual_state_management():
+ """Example: Manually managing bot detection state."""
+
+ config = GitHubRunnerConfig(
+ token="ghp_user_token",
+ repo="owner/repo",
+ bot_token="ghp_bot_token",
+ review_own_prs=False,
+ )
+
+ orchestrator = GitHubOrchestrator(
+ project_dir=Path("/path/to/project"),
+ config=config,
+ )
+
+ detector = orchestrator.bot_detector
+
+ # Manually check if PR should be skipped
+ pr_data = {"author": {"login": "alice"}}
+ commits = [
+ {"author": {"login": "alice"}, "oid": "abc123"},
+ {"author": {"login": "alice"}, "oid": "def456"},
+ ]
+
+ should_skip, reason = detector.should_skip_pr_review(
+ pr_number=789,
+ pr_data=pr_data,
+ commits=commits,
+ )
+
+ if should_skip:
+ print(f"Skipping PR #789: {reason}")
+ else:
+ print("PR #789 is safe to review")
+ # Proceed with review...
+ # After review:
+ detector.mark_reviewed(789, "abc123")
+
+ # Clear state when PR is closed/merged
+ detector.clear_pr_state(789)
+
+
+def example_configuration_options():
+ """Example: Different configuration scenarios."""
+
+ # Option 1: Strict bot detection (recommended)
+ strict_config = GitHubRunnerConfig(
+ token="ghp_user_token",
+ repo="owner/repo",
+ bot_token="ghp_bot_token",
+ review_own_prs=False, # Bot cannot review own PRs
+ )
+
+ # Option 2: Allow bot self-review (testing only)
+ permissive_config = GitHubRunnerConfig(
+ token="ghp_user_token",
+ repo="owner/repo",
+ bot_token="ghp_bot_token",
+ review_own_prs=True, # Bot CAN review own PRs
+ )
+
+ # Option 3: No bot detection (no bot token)
+ no_detection_config = GitHubRunnerConfig(
+ token="ghp_user_token",
+ repo="owner/repo",
+ bot_token=None, # No bot identification
+ review_own_prs=False,
+ )
+
+ print("Strict config:", strict_config.review_own_prs)
+ print("Permissive config:", permissive_config.review_own_prs)
+ print("No detection config:", no_detection_config.bot_token)
+
+
+if __name__ == "__main__":
+ print("Bot Detection Integration Examples\n")
+
+ print("\n1. Configuration Options")
+ print("=" * 50)
+ example_configuration_options()
+
+ print("\n2. With Bot Detection (requires GitHub setup)")
+ print("=" * 50)
+ print("Run: asyncio.run(example_with_bot_detection())")
+
+ print("\n3. Manual State Management")
+ print("=" * 50)
+ print("Run: asyncio.run(example_manual_state_management())")
diff --git a/apps/backend/runners/github/cleanup.py b/apps/backend/runners/github/cleanup.py
new file mode 100644
index 00000000..0accd67b
--- /dev/null
+++ b/apps/backend/runners/github/cleanup.py
@@ -0,0 +1,510 @@
+"""
+Data Retention & Cleanup
+========================
+
+Manages data retention, archival, and cleanup for the GitHub automation system.
+
+Features:
+- Configurable retention periods by state
+- Automatic archival of old records
+- Index pruning on startup
+- GDPR-compliant deletion (full purge)
+- Storage usage metrics
+
+Usage:
+ cleaner = DataCleaner(state_dir=Path(".auto-claude/github"))
+
+ # Run automatic cleanup
+ result = await cleaner.run_cleanup()
+ print(f"Cleaned {result.deleted_count} records")
+
+ # Purge specific issue/PR data
+ await cleaner.purge_issue(123)
+
+ # Get storage metrics
+ metrics = cleaner.get_storage_metrics()
+
+CLI:
+ python runner.py cleanup --older-than 90d
+ python runner.py cleanup --purge-issue 123
+"""
+
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass, field
+from datetime import datetime, timedelta, timezone
+from enum import Enum
+from pathlib import Path
+from typing import Any
+
+from .purge_strategy import PurgeResult, PurgeStrategy
+from .storage_metrics import StorageMetrics, StorageMetricsCalculator
+
+
+class RetentionPolicy(str, Enum):
+ """Retention policies for different record types."""
+
+ COMPLETED = "completed" # 90 days
+ FAILED = "failed" # 30 days
+ CANCELLED = "cancelled" # 7 days
+ STALE = "stale" # 14 days
+ ARCHIVED = "archived" # Indefinite (moved to archive)
+
+
+# Default retention periods in days
+DEFAULT_RETENTION = {
+ RetentionPolicy.COMPLETED: 90,
+ RetentionPolicy.FAILED: 30,
+ RetentionPolicy.CANCELLED: 7,
+ RetentionPolicy.STALE: 14,
+}
+
+
+@dataclass
+class RetentionConfig:
+ """
+ Configuration for data retention.
+ """
+
+ completed_days: int = 90
+ failed_days: int = 30
+ cancelled_days: int = 7
+ stale_days: int = 14
+ archive_enabled: bool = True
+ gdpr_mode: bool = False # If True, deletes instead of archives
+
+ def get_retention_days(self, policy: RetentionPolicy) -> int:
+ mapping = {
+ RetentionPolicy.COMPLETED: self.completed_days,
+ RetentionPolicy.FAILED: self.failed_days,
+ RetentionPolicy.CANCELLED: self.cancelled_days,
+ RetentionPolicy.STALE: self.stale_days,
+ RetentionPolicy.ARCHIVED: -1, # Never auto-delete
+ }
+ return mapping.get(policy, 90)
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "completed_days": self.completed_days,
+ "failed_days": self.failed_days,
+ "cancelled_days": self.cancelled_days,
+ "stale_days": self.stale_days,
+ "archive_enabled": self.archive_enabled,
+ "gdpr_mode": self.gdpr_mode,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict[str, Any]) -> RetentionConfig:
+ return cls(**{k: v for k, v in data.items() if k in cls.__dataclass_fields__})
+
+
+@dataclass
+class CleanupResult:
+ """
+ Result of a cleanup operation.
+ """
+
+ deleted_count: int = 0
+ archived_count: int = 0
+ pruned_index_entries: int = 0
+ freed_bytes: int = 0
+ errors: list[str] = field(default_factory=list)
+ started_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
+ completed_at: datetime | None = None
+ dry_run: bool = False
+
+ @property
+ def duration(self) -> timedelta | None:
+ if self.completed_at:
+ return self.completed_at - self.started_at
+ return None
+
+ @property
+ def freed_mb(self) -> float:
+ return self.freed_bytes / (1024 * 1024)
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "deleted_count": self.deleted_count,
+ "archived_count": self.archived_count,
+ "pruned_index_entries": self.pruned_index_entries,
+ "freed_bytes": self.freed_bytes,
+ "freed_mb": round(self.freed_mb, 2),
+ "errors": self.errors,
+ "started_at": self.started_at.isoformat(),
+ "completed_at": self.completed_at.isoformat()
+ if self.completed_at
+ else None,
+ "duration_seconds": self.duration.total_seconds()
+ if self.duration
+ else None,
+ "dry_run": self.dry_run,
+ }
+
+
+# StorageMetrics is now imported from storage_metrics.py
+
+
+class DataCleaner:
+ """
+ Manages data retention and cleanup.
+
+ Usage:
+ cleaner = DataCleaner(state_dir=Path(".auto-claude/github"))
+
+ # Check what would be cleaned
+ result = await cleaner.run_cleanup(dry_run=True)
+
+ # Actually clean
+ result = await cleaner.run_cleanup()
+
+ # Purge specific data (GDPR)
+ await cleaner.purge_issue(123)
+ """
+
+ def __init__(
+ self,
+ state_dir: Path,
+ config: RetentionConfig | None = None,
+ ):
+ """
+ Initialize data cleaner.
+
+ Args:
+ state_dir: Directory containing state files
+ config: Retention configuration
+ """
+ self.state_dir = state_dir
+ self.config = config or RetentionConfig()
+ self.archive_dir = state_dir / "archive"
+ self._storage_calculator = StorageMetricsCalculator(state_dir)
+ self._purge_strategy = PurgeStrategy(state_dir)
+
+ def get_storage_metrics(self) -> StorageMetrics:
+ """
+ Get current storage usage metrics.
+
+ Returns:
+ StorageMetrics with breakdown
+ """
+ return self._storage_calculator.calculate()
+
+ async def run_cleanup(
+ self,
+ dry_run: bool = False,
+ older_than_days: int | None = None,
+ ) -> CleanupResult:
+ """
+ Run cleanup based on retention policy.
+
+ Args:
+ dry_run: If True, only report what would be cleaned
+ older_than_days: Override retention days for all types
+
+ Returns:
+ CleanupResult with statistics
+ """
+ result = CleanupResult(dry_run=dry_run)
+ now = datetime.now(timezone.utc)
+
+ # Directories to clean
+ directories = [
+ (self.state_dir / "pr", "pr_reviews"),
+ (self.state_dir / "issues", "issues"),
+ (self.state_dir / "autofix", "autofix"),
+ ]
+
+ for dir_path, dir_type in directories:
+ if not dir_path.exists():
+ continue
+
+ for file_path in dir_path.glob("*.json"):
+ try:
+ cleaned = await self._process_file(
+ file_path, now, older_than_days, dry_run, result
+ )
+ if cleaned:
+ result.deleted_count += 1
+ except Exception as e:
+ result.errors.append(f"Error processing {file_path}: {e}")
+
+ # Prune indexes
+ await self._prune_indexes(dry_run, result)
+
+ # Clean up audit logs
+ await self._clean_audit_logs(now, older_than_days, dry_run, result)
+
+ result.completed_at = datetime.now(timezone.utc)
+ return result
+
+ async def _process_file(
+ self,
+ file_path: Path,
+ now: datetime,
+ older_than_days: int | None,
+ dry_run: bool,
+ result: CleanupResult,
+ ) -> bool:
+ """Process a single file for cleanup."""
+ try:
+ with open(file_path) as f:
+ data = json.load(f)
+ except (OSError, json.JSONDecodeError):
+ # Corrupted file, mark for deletion
+ if not dry_run:
+ file_size = file_path.stat().st_size
+ file_path.unlink()
+ result.freed_bytes += file_size
+ return True
+
+ # Get status and timestamp
+ status = data.get("status", "completed").lower()
+ updated_at = data.get("updated_at") or data.get("created_at")
+
+ if not updated_at:
+ return False
+
+ try:
+ record_time = datetime.fromisoformat(updated_at.replace("Z", "+00:00"))
+ except ValueError:
+ return False
+
+ # Determine retention policy
+ policy = self._get_policy_for_status(status)
+ retention_days = older_than_days or self.config.get_retention_days(policy)
+
+ if retention_days < 0:
+ return False # Never delete
+
+ cutoff = now - timedelta(days=retention_days)
+
+ if record_time < cutoff:
+ file_size = file_path.stat().st_size
+
+ if not dry_run:
+ if self.config.archive_enabled and not self.config.gdpr_mode:
+ # Archive instead of delete
+ await self._archive_file(file_path, data)
+ result.archived_count += 1
+ else:
+ # Delete
+ file_path.unlink()
+
+ result.freed_bytes += file_size
+
+ return True
+
+ return False
+
+ def _get_policy_for_status(self, status: str) -> RetentionPolicy:
+ """Map status to retention policy."""
+ status_map = {
+ "completed": RetentionPolicy.COMPLETED,
+ "merged": RetentionPolicy.COMPLETED,
+ "closed": RetentionPolicy.COMPLETED,
+ "failed": RetentionPolicy.FAILED,
+ "error": RetentionPolicy.FAILED,
+ "cancelled": RetentionPolicy.CANCELLED,
+ "stale": RetentionPolicy.STALE,
+ "abandoned": RetentionPolicy.STALE,
+ }
+ return status_map.get(status, RetentionPolicy.COMPLETED)
+
+ async def _archive_file(
+ self,
+ file_path: Path,
+ data: dict[str, Any],
+ ) -> None:
+ """Archive a file instead of deleting."""
+ # Create archive directory structure
+ relative = file_path.relative_to(self.state_dir)
+ archive_path = self.archive_dir / relative
+
+ archive_path.parent.mkdir(parents=True, exist_ok=True)
+
+ # Add archive metadata
+ data["_archived_at"] = datetime.now(timezone.utc).isoformat()
+ data["_original_path"] = str(file_path)
+
+ with open(archive_path, "w") as f:
+ json.dump(data, f, indent=2)
+
+ # Remove original
+ file_path.unlink()
+
+ async def _prune_indexes(
+ self,
+ dry_run: bool,
+ result: CleanupResult,
+ ) -> None:
+ """Prune stale entries from index files."""
+ index_files = [
+ self.state_dir / "pr" / "index.json",
+ self.state_dir / "issues" / "index.json",
+ self.state_dir / "autofix" / "index.json",
+ ]
+
+ for index_path in index_files:
+ if not index_path.exists():
+ continue
+
+ try:
+ with open(index_path) as f:
+ index_data = json.load(f)
+
+ if not isinstance(index_data, dict):
+ continue
+
+ items = index_data.get("items", {})
+ if not isinstance(items, dict):
+ continue
+
+ pruned = 0
+ to_remove = []
+
+ for key, entry in items.items():
+ # Check if referenced file exists
+ file_path = entry.get("file_path") or entry.get("path")
+ if file_path:
+ if not Path(file_path).exists():
+ to_remove.append(key)
+ pruned += 1
+
+ if to_remove and not dry_run:
+ for key in to_remove:
+ del items[key]
+
+ with open(index_path, "w") as f:
+ json.dump(index_data, f, indent=2)
+
+ result.pruned_index_entries += pruned
+
+ except (OSError, json.JSONDecodeError, KeyError):
+ result.errors.append(f"Error pruning index: {index_path}")
+
+ async def _clean_audit_logs(
+ self,
+ now: datetime,
+ older_than_days: int | None,
+ dry_run: bool,
+ result: CleanupResult,
+ ) -> None:
+ """Clean old audit logs."""
+ audit_dir = self.state_dir / "audit"
+ if not audit_dir.exists():
+ return
+
+ # Default 30 day retention for audit logs (overridable)
+ retention_days = older_than_days or 30
+ cutoff = now - timedelta(days=retention_days)
+
+ for log_file in audit_dir.glob("*.log"):
+ try:
+ # Check file modification time
+ mtime = datetime.fromtimestamp(
+ log_file.stat().st_mtime, tz=timezone.utc
+ )
+ if mtime < cutoff:
+ file_size = log_file.stat().st_size
+ if not dry_run:
+ log_file.unlink()
+ result.freed_bytes += file_size
+ result.deleted_count += 1
+ except OSError as e:
+ result.errors.append(f"Error cleaning audit log {log_file}: {e}")
+
+ async def purge_issue(
+ self,
+ issue_number: int,
+ repo: str | None = None,
+ ) -> CleanupResult:
+ """
+ Purge all data for a specific issue (GDPR-compliant).
+
+ Args:
+ issue_number: Issue number to purge
+ repo: Optional repository filter
+
+ Returns:
+ CleanupResult
+ """
+ purge_result = await self._purge_strategy.purge_by_criteria(
+ pattern="issue",
+ key="issue_number",
+ value=issue_number,
+ repo=repo,
+ )
+
+ # Convert PurgeResult to CleanupResult
+ return self._convert_purge_result(purge_result)
+
+ async def purge_pr(
+ self,
+ pr_number: int,
+ repo: str | None = None,
+ ) -> CleanupResult:
+ """
+ Purge all data for a specific PR (GDPR-compliant).
+
+ Args:
+ pr_number: PR number to purge
+ repo: Optional repository filter
+
+ Returns:
+ CleanupResult
+ """
+ purge_result = await self._purge_strategy.purge_by_criteria(
+ pattern="pr",
+ key="pr_number",
+ value=pr_number,
+ repo=repo,
+ )
+
+ # Convert PurgeResult to CleanupResult
+ return self._convert_purge_result(purge_result)
+
+ async def purge_repo(self, repo: str) -> CleanupResult:
+ """
+ Purge all data for a specific repository.
+
+ Args:
+ repo: Repository in owner/repo format
+
+ Returns:
+ CleanupResult
+ """
+ purge_result = await self._purge_strategy.purge_repository(repo)
+
+ # Convert PurgeResult to CleanupResult
+ return self._convert_purge_result(purge_result)
+
+ def _convert_purge_result(self, purge_result: PurgeResult) -> CleanupResult:
+ """
+ Convert PurgeResult to CleanupResult.
+
+ Args:
+ purge_result: PurgeResult from PurgeStrategy
+
+ Returns:
+ CleanupResult for DataCleaner API compatibility
+ """
+ cleanup_result = CleanupResult(
+ deleted_count=purge_result.deleted_count,
+ freed_bytes=purge_result.freed_bytes,
+ errors=purge_result.errors,
+ started_at=purge_result.started_at,
+ completed_at=purge_result.completed_at,
+ )
+ return cleanup_result
+
+ def get_retention_summary(self) -> dict[str, Any]:
+ """Get summary of retention settings and usage."""
+ metrics = self.get_storage_metrics()
+
+ return {
+ "config": self.config.to_dict(),
+ "storage": metrics.to_dict(),
+ "archive_enabled": self.config.archive_enabled,
+ "gdpr_mode": self.config.gdpr_mode,
+ }
diff --git a/apps/backend/runners/github/confidence.py b/apps/backend/runners/github/confidence.py
new file mode 100644
index 00000000..0e21b211
--- /dev/null
+++ b/apps/backend/runners/github/confidence.py
@@ -0,0 +1,562 @@
+"""
+Review Confidence Scoring
+=========================
+
+Adds confidence scores to review findings to help users prioritize.
+
+Features:
+- Confidence scoring based on pattern matching, historical accuracy
+- Risk assessment (false positive likelihood)
+- Evidence tracking for transparency
+- Calibration based on outcome tracking
+
+Usage:
+ scorer = ConfidenceScorer(learning_tracker=tracker)
+
+ # Score a finding
+ scored = scorer.score_finding(finding, context)
+ print(f"Confidence: {scored.confidence}%")
+ print(f"False positive risk: {scored.false_positive_risk}")
+
+ # Get explanation
+ print(scorer.explain_confidence(scored))
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from enum import Enum
+from typing import Any
+
+# Import learning tracker if available
+try:
+ from .learning import LearningPattern, LearningTracker
+except (ImportError, ValueError, SystemError):
+ LearningTracker = None
+ LearningPattern = None
+
+
+class FalsePositiveRisk(str, Enum):
+ """Likelihood that a finding is a false positive."""
+
+ LOW = "low" # <10% chance
+ MEDIUM = "medium" # 10-30% chance
+ HIGH = "high" # >30% chance
+ UNKNOWN = "unknown"
+
+
+class ConfidenceLevel(str, Enum):
+ """Confidence level categories."""
+
+ VERY_HIGH = "very_high" # 90%+
+ HIGH = "high" # 75-90%
+ MEDIUM = "medium" # 50-75%
+ LOW = "low" # <50%
+
+
+@dataclass
+class ConfidenceFactors:
+ """
+ Factors that contribute to confidence score.
+ """
+
+ # Pattern-based factors
+ pattern_matches: int = 0 # Similar patterns found
+ pattern_accuracy: float = 0.0 # Historical accuracy of this pattern
+
+ # Context factors
+ file_type_accuracy: float = 0.0 # Accuracy for this file type
+ category_accuracy: float = 0.0 # Accuracy for this category
+
+ # Evidence factors
+ code_evidence_count: int = 0 # Code references supporting finding
+ similar_findings_count: int = 0 # Similar findings in codebase
+
+ # Historical factors
+ historical_sample_size: int = 0 # How many similar cases we've seen
+ historical_accuracy: float = 0.0 # Accuracy on similar cases
+
+ # Severity factors
+ severity_weight: float = 1.0 # Higher severity = more scrutiny
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "pattern_matches": self.pattern_matches,
+ "pattern_accuracy": self.pattern_accuracy,
+ "file_type_accuracy": self.file_type_accuracy,
+ "category_accuracy": self.category_accuracy,
+ "code_evidence_count": self.code_evidence_count,
+ "similar_findings_count": self.similar_findings_count,
+ "historical_sample_size": self.historical_sample_size,
+ "historical_accuracy": self.historical_accuracy,
+ "severity_weight": self.severity_weight,
+ }
+
+
+@dataclass
+class ScoredFinding:
+ """
+ A finding with confidence scoring.
+ """
+
+ finding_id: str
+ original_finding: dict[str, Any]
+
+ # Confidence score (0-100)
+ confidence: float
+ confidence_level: ConfidenceLevel
+
+ # False positive risk
+ false_positive_risk: FalsePositiveRisk
+
+ # Factors that contributed
+ factors: ConfidenceFactors
+
+ # Evidence for the finding
+ evidence: list[str] = field(default_factory=list)
+
+ # Explanation basis
+ explanation_basis: str = ""
+
+ @property
+ def is_high_confidence(self) -> bool:
+ return self.confidence >= 75.0
+
+ @property
+ def should_highlight(self) -> bool:
+ """Should this finding be highlighted to the user?"""
+ return (
+ self.is_high_confidence
+ and self.false_positive_risk != FalsePositiveRisk.HIGH
+ )
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "finding_id": self.finding_id,
+ "original_finding": self.original_finding,
+ "confidence": self.confidence,
+ "confidence_level": self.confidence_level.value,
+ "false_positive_risk": self.false_positive_risk.value,
+ "factors": self.factors.to_dict(),
+ "evidence": self.evidence,
+ "explanation_basis": self.explanation_basis,
+ }
+
+
+@dataclass
+class ReviewContext:
+ """
+ Context for scoring a review.
+ """
+
+ file_types: list[str] = field(default_factory=list)
+ categories: list[str] = field(default_factory=list)
+ change_size: str = "medium" # small/medium/large
+ pr_author: str = ""
+ is_external_contributor: bool = False
+
+
+class ConfidenceScorer:
+ """
+ Scores confidence for review findings.
+
+ Uses historical data, pattern matching, and evidence to provide
+ calibrated confidence scores.
+ """
+
+ # Base weights for different factors
+ PATTERN_WEIGHT = 0.25
+ HISTORY_WEIGHT = 0.30
+ EVIDENCE_WEIGHT = 0.25
+ CATEGORY_WEIGHT = 0.20
+
+ # Minimum sample size for reliable historical data
+ MIN_SAMPLE_SIZE = 10
+
+ def __init__(
+ self,
+ learning_tracker: Any | None = None,
+ patterns: list[Any] | None = None,
+ ):
+ """
+ Initialize confidence scorer.
+
+ Args:
+ learning_tracker: LearningTracker for historical data
+ patterns: Pre-computed patterns for scoring
+ """
+ self.learning_tracker = learning_tracker
+ self.patterns = patterns or []
+
+ def score_finding(
+ self,
+ finding: dict[str, Any],
+ context: ReviewContext | None = None,
+ ) -> ScoredFinding:
+ """
+ Score confidence for a single finding.
+
+ Args:
+ finding: The finding to score
+ context: Review context
+
+ Returns:
+ ScoredFinding with confidence score
+ """
+ context = context or ReviewContext()
+ factors = ConfidenceFactors()
+
+ # Extract finding metadata
+ finding_id = finding.get("id", str(hash(str(finding))))
+ severity = finding.get("severity", "medium")
+ category = finding.get("category", "")
+ file_path = finding.get("file", "")
+ evidence = finding.get("evidence", [])
+
+ # Set severity weight
+ severity_weights = {
+ "critical": 1.2,
+ "high": 1.1,
+ "medium": 1.0,
+ "low": 0.9,
+ "info": 0.8,
+ }
+ factors.severity_weight = severity_weights.get(severity.lower(), 1.0)
+
+ # Score based on evidence
+ factors.code_evidence_count = len(evidence)
+ evidence_score = min(1.0, len(evidence) * 0.2) # Up to 5 pieces = 100%
+
+ # Score based on patterns
+ pattern_score = self._score_patterns(category, file_path, context, factors)
+
+ # Score based on historical accuracy
+ history_score = self._score_history(category, context, factors)
+
+ # Score based on category
+ category_score = self._score_category(category, factors)
+
+ # Calculate weighted confidence
+ raw_confidence = (
+ pattern_score * self.PATTERN_WEIGHT
+ + history_score * self.HISTORY_WEIGHT
+ + evidence_score * self.EVIDENCE_WEIGHT
+ + category_score * self.CATEGORY_WEIGHT
+ )
+
+ # Apply severity weight
+ raw_confidence *= factors.severity_weight
+
+ # Convert to 0-100 scale
+ confidence = min(100.0, max(0.0, raw_confidence * 100))
+
+ # Determine confidence level
+ if confidence >= 90:
+ confidence_level = ConfidenceLevel.VERY_HIGH
+ elif confidence >= 75:
+ confidence_level = ConfidenceLevel.HIGH
+ elif confidence >= 50:
+ confidence_level = ConfidenceLevel.MEDIUM
+ else:
+ confidence_level = ConfidenceLevel.LOW
+
+ # Determine false positive risk
+ false_positive_risk = self._assess_false_positive_risk(
+ confidence, factors, context
+ )
+
+ # Build explanation basis
+ explanation_basis = self._build_explanation(factors, context)
+
+ return ScoredFinding(
+ finding_id=finding_id,
+ original_finding=finding,
+ confidence=round(confidence, 1),
+ confidence_level=confidence_level,
+ false_positive_risk=false_positive_risk,
+ factors=factors,
+ evidence=evidence,
+ explanation_basis=explanation_basis,
+ )
+
+ def score_findings(
+ self,
+ findings: list[dict[str, Any]],
+ context: ReviewContext | None = None,
+ ) -> list[ScoredFinding]:
+ """
+ Score multiple findings.
+
+ Args:
+ findings: List of findings
+ context: Review context
+
+ Returns:
+ List of scored findings, sorted by confidence
+ """
+ scored = [self.score_finding(f, context) for f in findings]
+ # Sort by confidence descending
+ scored.sort(key=lambda s: s.confidence, reverse=True)
+ return scored
+
+ def _score_patterns(
+ self,
+ category: str,
+ file_path: str,
+ context: ReviewContext,
+ factors: ConfidenceFactors,
+ ) -> float:
+ """Score based on pattern matching."""
+ if not self.patterns:
+ return 0.5 # Neutral if no patterns
+
+ matches = 0
+ total_accuracy = 0.0
+
+ # Get file extension
+ file_ext = file_path.split(".")[-1] if "." in file_path else ""
+
+ for pattern in self.patterns:
+ pattern_type = getattr(
+ pattern, "pattern_type", pattern.get("pattern_type", "")
+ )
+ pattern_context = getattr(pattern, "context", pattern.get("context", {}))
+ pattern_accuracy = getattr(
+ pattern, "accuracy", pattern.get("accuracy", 0.5)
+ )
+
+ # Check for file type match
+ if pattern_type == "file_type_accuracy":
+ if pattern_context.get("file_type") == file_ext:
+ matches += 1
+ total_accuracy += pattern_accuracy
+ factors.file_type_accuracy = pattern_accuracy
+
+ # Check for category match
+ if pattern_type == "category_accuracy":
+ if pattern_context.get("category") == category:
+ matches += 1
+ total_accuracy += pattern_accuracy
+ factors.category_accuracy = pattern_accuracy
+
+ factors.pattern_matches = matches
+
+ if matches > 0:
+ factors.pattern_accuracy = total_accuracy / matches
+ return factors.pattern_accuracy
+
+ return 0.5 # Neutral if no matches
+
+ def _score_history(
+ self,
+ category: str,
+ context: ReviewContext,
+ factors: ConfidenceFactors,
+ ) -> float:
+ """Score based on historical accuracy."""
+ if not self.learning_tracker:
+ return 0.5 # Neutral if no history
+
+ try:
+ # Get accuracy stats
+ stats = self.learning_tracker.get_accuracy()
+ factors.historical_sample_size = stats.total_predictions
+
+ if stats.total_predictions >= self.MIN_SAMPLE_SIZE:
+ factors.historical_accuracy = stats.accuracy
+ return stats.accuracy
+ else:
+ # Not enough data, return neutral with penalty
+ return 0.5 * (stats.total_predictions / self.MIN_SAMPLE_SIZE)
+
+ except Exception as e:
+ # Log the error for debugging while returning neutral score
+ import logging
+
+ logging.getLogger(__name__).warning(
+ f"Error scoring history for category '{category}': {e}"
+ )
+ return 0.5
+
+ def _score_category(
+ self,
+ category: str,
+ factors: ConfidenceFactors,
+ ) -> float:
+ """Score based on category reliability."""
+ # Categories with higher inherent confidence
+ high_confidence_categories = {
+ "security": 0.85,
+ "bug": 0.75,
+ "error_handling": 0.70,
+ "performance": 0.65,
+ }
+
+ # Categories with lower inherent confidence
+ low_confidence_categories = {
+ "style": 0.50,
+ "naming": 0.45,
+ "documentation": 0.40,
+ "nitpick": 0.35,
+ }
+
+ if category.lower() in high_confidence_categories:
+ return high_confidence_categories[category.lower()]
+ elif category.lower() in low_confidence_categories:
+ return low_confidence_categories[category.lower()]
+
+ return 0.6 # Default for unknown categories
+
+ def _assess_false_positive_risk(
+ self,
+ confidence: float,
+ factors: ConfidenceFactors,
+ context: ReviewContext,
+ ) -> FalsePositiveRisk:
+ """Assess risk of false positive."""
+ # Low confidence = high false positive risk
+ if confidence < 50:
+ return FalsePositiveRisk.HIGH
+ elif confidence < 75:
+ # Check additional factors
+ if factors.historical_sample_size < self.MIN_SAMPLE_SIZE:
+ return FalsePositiveRisk.HIGH
+ elif factors.historical_accuracy < 0.7:
+ return FalsePositiveRisk.MEDIUM
+ else:
+ return FalsePositiveRisk.MEDIUM
+ else:
+ # High confidence
+ if factors.code_evidence_count >= 3:
+ return FalsePositiveRisk.LOW
+ elif factors.historical_accuracy >= 0.85:
+ return FalsePositiveRisk.LOW
+ else:
+ return FalsePositiveRisk.MEDIUM
+
+ def _build_explanation(
+ self,
+ factors: ConfidenceFactors,
+ context: ReviewContext,
+ ) -> str:
+ """Build explanation for confidence score."""
+ parts = []
+
+ if factors.historical_sample_size > 0:
+ parts.append(
+ f"Based on {factors.historical_sample_size} similar patterns "
+ f"with {factors.historical_accuracy * 100:.0f}% accuracy"
+ )
+
+ if factors.pattern_matches > 0:
+ parts.append(f"Matched {factors.pattern_matches} known patterns")
+
+ if factors.code_evidence_count > 0:
+ parts.append(f"Supported by {factors.code_evidence_count} code references")
+
+ if not parts:
+ parts.append("Initial assessment without historical data")
+
+ return ". ".join(parts)
+
+ def explain_confidence(self, scored: ScoredFinding) -> str:
+ """
+ Get a human-readable explanation of the confidence score.
+
+ Args:
+ scored: The scored finding
+
+ Returns:
+ Explanation string
+ """
+ lines = [
+ f"Confidence: {scored.confidence}% ({scored.confidence_level.value})",
+ f"False positive risk: {scored.false_positive_risk.value}",
+ "",
+ "Basis:",
+ f" {scored.explanation_basis}",
+ ]
+
+ if scored.factors.historical_sample_size > 0:
+ lines.append(
+ f" Historical accuracy: {scored.factors.historical_accuracy * 100:.0f}% "
+ f"({scored.factors.historical_sample_size} samples)"
+ )
+
+ if scored.evidence:
+ lines.append(f" Evidence: {len(scored.evidence)} code references")
+
+ return "\n".join(lines)
+
+ def filter_by_confidence(
+ self,
+ scored_findings: list[ScoredFinding],
+ min_confidence: float = 50.0,
+ exclude_high_fp_risk: bool = False,
+ ) -> list[ScoredFinding]:
+ """
+ Filter findings by confidence threshold.
+
+ Args:
+ scored_findings: List of scored findings
+ min_confidence: Minimum confidence to include
+ exclude_high_fp_risk: Exclude high false positive risk
+
+ Returns:
+ Filtered list
+ """
+ result = []
+ for finding in scored_findings:
+ if finding.confidence < min_confidence:
+ continue
+ if (
+ exclude_high_fp_risk
+ and finding.false_positive_risk == FalsePositiveRisk.HIGH
+ ):
+ continue
+ result.append(finding)
+ return result
+
+ def get_summary(
+ self,
+ scored_findings: list[ScoredFinding],
+ ) -> dict[str, Any]:
+ """
+ Get summary statistics for scored findings.
+
+ Args:
+ scored_findings: List of scored findings
+
+ Returns:
+ Summary dict
+ """
+ if not scored_findings:
+ return {
+ "total": 0,
+ "avg_confidence": 0.0,
+ "by_level": {},
+ "by_risk": {},
+ }
+
+ by_level: dict[str, int] = {}
+ by_risk: dict[str, int] = {}
+ total_confidence = 0.0
+
+ for finding in scored_findings:
+ level = finding.confidence_level.value
+ by_level[level] = by_level.get(level, 0) + 1
+
+ risk = finding.false_positive_risk.value
+ by_risk[risk] = by_risk.get(risk, 0) + 1
+
+ total_confidence += finding.confidence
+
+ return {
+ "total": len(scored_findings),
+ "avg_confidence": total_confidence / len(scored_findings),
+ "by_level": by_level,
+ "by_risk": by_risk,
+ "high_confidence_count": by_level.get("very_high", 0)
+ + by_level.get("high", 0),
+ "low_risk_count": by_risk.get("low", 0),
+ }
diff --git a/apps/backend/runners/github/context_gatherer.py b/apps/backend/runners/github/context_gatherer.py
new file mode 100644
index 00000000..00374bbd
--- /dev/null
+++ b/apps/backend/runners/github/context_gatherer.py
@@ -0,0 +1,897 @@
+"""
+PR Context Gatherer
+===================
+
+Pre-review context gathering phase that collects all necessary information
+BEFORE the AI review agent starts. This ensures all context is available
+inline without requiring the AI to make additional API calls.
+
+Responsibilities:
+- Fetch PR metadata (title, author, branches, description)
+- Get all changed files with full content
+- Detect monorepo structure and project layout
+- Find related files (imports, tests, configs)
+- Build complete diff with context
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import re
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import TYPE_CHECKING
+
+try:
+ from .gh_client import GHClient, PRTooLargeError
+except (ImportError, ValueError, SystemError):
+ from gh_client import GHClient, PRTooLargeError
+
+if TYPE_CHECKING:
+ try:
+ from .models import FollowupReviewContext, PRReviewResult
+ except (ImportError, ValueError, SystemError):
+ from models import FollowupReviewContext, PRReviewResult
+
+
+@dataclass
+class ChangedFile:
+ """A file that was changed in the PR."""
+
+ path: str
+ status: str # added, modified, deleted, renamed
+ additions: int
+ deletions: int
+ content: str # Current file content
+ base_content: str # Content before changes (for comparison)
+ patch: str # The diff patch for this file
+
+
+@dataclass
+class AIBotComment:
+ """A comment from an AI review tool (CodeRabbit, Cursor, Greptile, etc.)."""
+
+ comment_id: int
+ author: str
+ tool_name: str # "CodeRabbit", "Cursor", "Greptile", etc.
+ body: str
+ file: str | None # File path if it's a file-level comment
+ line: int | None # Line number if it's an inline comment
+ created_at: str
+
+
+# Known AI code review bots and their display names
+AI_BOT_PATTERNS: dict[str, str] = {
+ "coderabbitai": "CodeRabbit",
+ "coderabbit-ai": "CodeRabbit",
+ "coderabbit[bot]": "CodeRabbit",
+ "greptile": "Greptile",
+ "greptile[bot]": "Greptile",
+ "cursor-ai": "Cursor",
+ "cursor[bot]": "Cursor",
+ "sourcery-ai": "Sourcery",
+ "sourcery-ai[bot]": "Sourcery",
+ "codiumai": "Qodo",
+ "codium-ai[bot]": "Qodo",
+ "qodo-merge-bot": "Qodo",
+ "copilot": "GitHub Copilot",
+ "copilot[bot]": "GitHub Copilot",
+ "github-actions": "GitHub Actions",
+ "github-actions[bot]": "GitHub Actions",
+ "deepsource-autofix": "DeepSource",
+ "deepsource-autofix[bot]": "DeepSource",
+ "sonarcloud": "SonarCloud",
+ "sonarcloud[bot]": "SonarCloud",
+}
+
+
+@dataclass
+class PRContext:
+ """Complete context for PR review."""
+
+ pr_number: int
+ title: str
+ description: str
+ author: str
+ base_branch: str
+ head_branch: str
+ state: str # PR state: open, closed, merged
+ changed_files: list[ChangedFile]
+ diff: str
+ repo_structure: str # Description of monorepo layout
+ related_files: list[str] # Imports, tests, etc.
+ commits: list[dict] = field(default_factory=list)
+ labels: list[str] = field(default_factory=list)
+ total_additions: int = 0
+ total_deletions: int = 0
+ # NEW: AI tool comments for triage
+ ai_bot_comments: list[AIBotComment] = field(default_factory=list)
+ # Flag indicating if full diff was skipped (PR > 20K lines)
+ diff_truncated: bool = False
+
+
+class PRContextGatherer:
+ """Gathers all context needed for PR review BEFORE the AI starts."""
+
+ def __init__(self, project_dir: Path, pr_number: int):
+ self.project_dir = Path(project_dir)
+ self.pr_number = pr_number
+ self.gh_client = GHClient(
+ project_dir=self.project_dir,
+ default_timeout=30.0,
+ max_retries=3,
+ )
+
+ async def gather(self) -> PRContext:
+ """
+ Gather all context for review.
+
+ Returns:
+ PRContext with all necessary information for review
+ """
+ print(f"[Context] Gathering context for PR #{self.pr_number}...", flush=True)
+
+ # Fetch basic PR metadata
+ pr_data = await self._fetch_pr_metadata()
+ print(
+ f"[Context] PR metadata: {pr_data['title']} by {pr_data['author']['login']}",
+ flush=True,
+ )
+
+ # Fetch changed files with content
+ changed_files = await self._fetch_changed_files(pr_data)
+ print(f"[Context] Fetched {len(changed_files)} changed files", flush=True)
+
+ # Fetch full diff
+ diff = await self._fetch_pr_diff()
+ print(f"[Context] Fetched diff: {len(diff)} chars", flush=True)
+
+ # Detect repo structure
+ repo_structure = self._detect_repo_structure()
+ print("[Context] Detected repo structure", flush=True)
+
+ # Find related files
+ related_files = self._find_related_files(changed_files)
+ print(f"[Context] Found {len(related_files)} related files", flush=True)
+
+ # Fetch commits
+ commits = await self._fetch_commits()
+ print(f"[Context] Fetched {len(commits)} commits", flush=True)
+
+ # Fetch AI bot comments for triage
+ ai_bot_comments = await self._fetch_ai_bot_comments()
+ print(f"[Context] Fetched {len(ai_bot_comments)} AI bot comments", flush=True)
+
+ # Check if diff was truncated (empty diff but files were changed)
+ diff_truncated = len(diff) == 0 and len(changed_files) > 0
+
+ return PRContext(
+ pr_number=self.pr_number,
+ title=pr_data["title"],
+ description=pr_data.get("body", ""),
+ author=pr_data["author"]["login"],
+ base_branch=pr_data["baseRefName"],
+ head_branch=pr_data["headRefName"],
+ state=pr_data.get("state", "open"),
+ changed_files=changed_files,
+ diff=diff,
+ repo_structure=repo_structure,
+ related_files=related_files,
+ commits=commits,
+ labels=[label["name"] for label in pr_data.get("labels", [])],
+ total_additions=pr_data.get("additions", 0),
+ total_deletions=pr_data.get("deletions", 0),
+ ai_bot_comments=ai_bot_comments,
+ diff_truncated=diff_truncated,
+ )
+
+ async def _fetch_pr_metadata(self) -> dict:
+ """Fetch PR metadata from GitHub API via gh CLI."""
+ return await self.gh_client.pr_get(
+ self.pr_number,
+ json_fields=[
+ "number",
+ "title",
+ "body",
+ "state",
+ "headRefName",
+ "baseRefName",
+ "author",
+ "files",
+ "additions",
+ "deletions",
+ "changedFiles",
+ "labels",
+ ],
+ )
+
+ async def _fetch_changed_files(self, pr_data: dict) -> list[ChangedFile]:
+ """
+ Fetch all changed files with their full content.
+
+ For each file, we need:
+ - Current content (HEAD of PR branch)
+ - Base content (before changes)
+ - Diff patch
+ """
+ changed_files = []
+ files = pr_data.get("files", [])
+
+ for file_info in files:
+ path = file_info["path"]
+ status = self._normalize_status(file_info.get("status", "modified"))
+ additions = file_info.get("additions", 0)
+ deletions = file_info.get("deletions", 0)
+
+ print(f"[Context] Processing {path} ({status})...", flush=True)
+
+ # Get current content (from PR head branch)
+ content = await self._read_file_content(path, pr_data["headRefName"])
+
+ # Get base content (from base branch)
+ base_content = await self._read_file_content(path, pr_data["baseRefName"])
+
+ # Get the patch for this specific file
+ patch = await self._get_file_patch(
+ path, pr_data["baseRefName"], pr_data["headRefName"]
+ )
+
+ changed_files.append(
+ ChangedFile(
+ path=path,
+ status=status,
+ additions=additions,
+ deletions=deletions,
+ content=content,
+ base_content=base_content,
+ patch=patch,
+ )
+ )
+
+ return changed_files
+
+ def _normalize_status(self, status: str) -> str:
+ """Normalize file status to standard values."""
+ status_lower = status.lower()
+ if status_lower in ["added", "add"]:
+ return "added"
+ elif status_lower in ["modified", "mod", "changed"]:
+ return "modified"
+ elif status_lower in ["deleted", "del", "removed"]:
+ return "deleted"
+ elif status_lower in ["renamed", "rename"]:
+ return "renamed"
+ else:
+ return status_lower
+
+ async def _read_file_content(self, path: str, ref: str) -> str:
+ """
+ Read file content from a specific git ref.
+
+ Args:
+ path: File path relative to repo root
+ ref: Git ref (branch name, commit hash, etc.)
+
+ Returns:
+ File content as string, or empty string if file doesn't exist
+ """
+ try:
+ proc = await asyncio.create_subprocess_exec(
+ "git",
+ "show",
+ f"{ref}:{path}",
+ cwd=self.project_dir,
+ stdout=asyncio.subprocess.PIPE,
+ stderr=asyncio.subprocess.PIPE,
+ )
+
+ stdout, stderr = await asyncio.wait_for(proc.communicate(), timeout=10.0)
+
+ # File might not exist in base branch (new file)
+ if proc.returncode != 0:
+ return ""
+
+ return stdout.decode("utf-8")
+ except asyncio.TimeoutError:
+ print(f"[Context] Timeout reading {path} from {ref}", flush=True)
+ return ""
+ except Exception as e:
+ print(f"[Context] Error reading {path} from {ref}: {e}", flush=True)
+ return ""
+
+ async def _get_file_patch(self, path: str, base_ref: str, head_ref: str) -> str:
+ """
+ Get the diff patch for a specific file using git diff.
+
+ Args:
+ path: File path relative to repo root
+ base_ref: Base branch ref
+ head_ref: Head branch ref
+
+ Returns:
+ Unified diff patch for this file
+ """
+ try:
+ proc = await asyncio.create_subprocess_exec(
+ "git",
+ "diff",
+ f"{base_ref}...{head_ref}",
+ "--",
+ path,
+ cwd=self.project_dir,
+ stdout=asyncio.subprocess.PIPE,
+ stderr=asyncio.subprocess.PIPE,
+ )
+
+ stdout, stderr = await asyncio.wait_for(proc.communicate(), timeout=10.0)
+
+ if proc.returncode != 0:
+ print(
+ f"[Context] Failed to get patch for {path}: {stderr.decode('utf-8')}",
+ flush=True,
+ )
+ return ""
+
+ return stdout.decode("utf-8")
+ except asyncio.TimeoutError:
+ print(f"[Context] Timeout getting patch for {path}", flush=True)
+ return ""
+ except Exception as e:
+ print(f"[Context] Error getting patch for {path}: {e}", flush=True)
+ return ""
+
+ async def _fetch_pr_diff(self) -> str:
+ """
+ Fetch complete PR diff from GitHub.
+
+ Returns empty string if PR exceeds GitHub's 20K line limit.
+ In this case, individual file patches from ChangedFile.patch should be used instead.
+ """
+ try:
+ return await self.gh_client.pr_diff(self.pr_number)
+ except PRTooLargeError as e:
+ print(f"[Context] Warning: {str(e)}", flush=True)
+ print(
+ "[Context] Skipping full diff - will use individual file patches",
+ flush=True,
+ )
+ return ""
+
+ async def _fetch_commits(self) -> list[dict]:
+ """Fetch commit history for this PR."""
+ try:
+ data = await self.gh_client.pr_get(self.pr_number, json_fields=["commits"])
+ return data.get("commits", [])
+ except Exception:
+ return []
+
+ async def _fetch_ai_bot_comments(self) -> list[AIBotComment]:
+ """
+ Fetch comments from AI code review tools on this PR.
+
+ Fetches both:
+ - Review comments (inline comments on files)
+ - Issue comments (general PR comments)
+
+ Returns comments from known AI tools like CodeRabbit, Cursor, Greptile, etc.
+ """
+ ai_comments: list[AIBotComment] = []
+
+ try:
+ # Fetch review comments (inline comments on files)
+ review_comments = await self._fetch_pr_review_comments()
+ for comment in review_comments:
+ ai_comment = self._parse_ai_comment(comment, is_review_comment=True)
+ if ai_comment:
+ ai_comments.append(ai_comment)
+
+ # Fetch issue comments (general PR comments)
+ issue_comments = await self._fetch_pr_issue_comments()
+ for comment in issue_comments:
+ ai_comment = self._parse_ai_comment(comment, is_review_comment=False)
+ if ai_comment:
+ ai_comments.append(ai_comment)
+
+ except Exception as e:
+ print(f"[Context] Error fetching AI bot comments: {e}", flush=True)
+
+ return ai_comments
+
+ def _parse_ai_comment(
+ self, comment: dict, is_review_comment: bool
+ ) -> AIBotComment | None:
+ """
+ Parse a comment and return AIBotComment if it's from a known AI tool.
+
+ Args:
+ comment: Raw comment data from GitHub API
+ is_review_comment: True for inline review comments, False for issue comments
+
+ Returns:
+ AIBotComment if author is a known AI bot, None otherwise
+ """
+ # Handle null author (deleted/suspended users return null from GitHub API)
+ author_data = comment.get("author")
+ author = (author_data.get("login", "") if author_data else "").lower()
+ if not author:
+ # Fallback for different API response formats
+ user_data = comment.get("user")
+ author = (user_data.get("login", "") if user_data else "").lower()
+
+ # Check if author matches any known AI bot pattern
+ tool_name = None
+ for pattern, name in AI_BOT_PATTERNS.items():
+ if pattern in author or author == pattern:
+ tool_name = name
+ break
+
+ if not tool_name:
+ return None
+
+ # Extract file and line info for review comments
+ file_path = None
+ line = None
+ if is_review_comment:
+ file_path = comment.get("path")
+ line = comment.get("line") or comment.get("original_line")
+
+ return AIBotComment(
+ comment_id=comment.get("id", 0),
+ author=author,
+ tool_name=tool_name,
+ body=comment.get("body", ""),
+ file=file_path,
+ line=line,
+ created_at=comment.get("createdAt", comment.get("created_at", "")),
+ )
+
+ async def _fetch_pr_review_comments(self) -> list[dict]:
+ """Fetch inline review comments on the PR."""
+ try:
+ result = await self.gh_client.run(
+ [
+ "api",
+ f"repos/{{owner}}/{{repo}}/pulls/{self.pr_number}/comments",
+ "--jq",
+ ".",
+ ],
+ raise_on_error=False,
+ )
+ if result.returncode == 0 and result.stdout.strip():
+ return json.loads(result.stdout)
+ return []
+ except Exception as e:
+ print(f"[Context] Error fetching review comments: {e}", flush=True)
+ return []
+
+ async def _fetch_pr_issue_comments(self) -> list[dict]:
+ """Fetch general issue comments on the PR."""
+ try:
+ result = await self.gh_client.run(
+ [
+ "api",
+ f"repos/{{owner}}/{{repo}}/issues/{self.pr_number}/comments",
+ "--jq",
+ ".",
+ ],
+ raise_on_error=False,
+ )
+ if result.returncode == 0 and result.stdout.strip():
+ return json.loads(result.stdout)
+ return []
+ except Exception as e:
+ print(f"[Context] Error fetching issue comments: {e}", flush=True)
+ return []
+
+ def _detect_repo_structure(self) -> str:
+ """
+ Detect and describe the repository structure.
+
+ Looks for common monorepo patterns and returns a human-readable
+ description that helps the AI understand the project layout.
+ """
+ structure_info = []
+
+ # Check for monorepo indicators
+ apps_dir = self.project_dir / "apps"
+ packages_dir = self.project_dir / "packages"
+ libs_dir = self.project_dir / "libs"
+
+ if apps_dir.exists():
+ apps = [
+ d.name
+ for d in apps_dir.iterdir()
+ if d.is_dir() and not d.name.startswith(".")
+ ]
+ if apps:
+ structure_info.append(f"**Monorepo Apps**: {', '.join(apps)}")
+
+ if packages_dir.exists():
+ packages = [
+ d.name
+ for d in packages_dir.iterdir()
+ if d.is_dir() and not d.name.startswith(".")
+ ]
+ if packages:
+ structure_info.append(f"**Packages**: {', '.join(packages)}")
+
+ if libs_dir.exists():
+ libs = [
+ d.name
+ for d in libs_dir.iterdir()
+ if d.is_dir() and not d.name.startswith(".")
+ ]
+ if libs:
+ structure_info.append(f"**Libraries**: {', '.join(libs)}")
+
+ # Check for package.json (Node.js)
+ if (self.project_dir / "package.json").exists():
+ try:
+ with open(self.project_dir / "package.json") as f:
+ pkg_data = json.load(f)
+ if "workspaces" in pkg_data:
+ structure_info.append(
+ f"**Workspaces**: {', '.join(pkg_data['workspaces'])}"
+ )
+ except (json.JSONDecodeError, KeyError):
+ pass
+
+ # Check for Python project structure
+ if (self.project_dir / "pyproject.toml").exists():
+ structure_info.append("**Python Project** (pyproject.toml)")
+
+ if (self.project_dir / "requirements.txt").exists():
+ structure_info.append("**Python** (requirements.txt)")
+
+ # Check for common framework indicators
+ if (self.project_dir / "angular.json").exists():
+ structure_info.append("**Framework**: Angular")
+ if (self.project_dir / "next.config.js").exists():
+ structure_info.append("**Framework**: Next.js")
+ if (self.project_dir / "nuxt.config.js").exists():
+ structure_info.append("**Framework**: Nuxt.js")
+ if (self.project_dir / "vite.config.ts").exists() or (
+ self.project_dir / "vite.config.js"
+ ).exists():
+ structure_info.append("**Build**: Vite")
+
+ # Check for Electron
+ if (self.project_dir / "electron.vite.config.ts").exists():
+ structure_info.append("**Electron** app")
+
+ if not structure_info:
+ return "**Structure**: Standard single-package repository"
+
+ return "\n".join(structure_info)
+
+ def _find_related_files(self, changed_files: list[ChangedFile]) -> list[str]:
+ """
+ Find files related to the changes.
+
+ This includes:
+ - Test files for changed source files
+ - Imported modules and dependencies
+ - Configuration files in the same directory
+ - Related type definition files
+ """
+ related = set()
+
+ for changed_file in changed_files:
+ path = Path(changed_file.path)
+
+ # Find test files
+ related.update(self._find_test_files(path))
+
+ # Find imported files (for supported languages)
+ if path.suffix in [".ts", ".tsx", ".js", ".jsx", ".py"]:
+ related.update(self._find_imports(changed_file.content, path))
+
+ # Find config files in same directory
+ related.update(self._find_config_files(path.parent))
+
+ # Find type definition files
+ if path.suffix in [".ts", ".tsx"]:
+ related.update(self._find_type_definitions(path))
+
+ # Remove files that are already in changed_files
+ changed_paths = {cf.path for cf in changed_files}
+ related = {r for r in related if r not in changed_paths}
+
+ # Limit to 20 most relevant files
+ return sorted(related)[:20]
+
+ def _find_test_files(self, source_path: Path) -> set[str]:
+ """Find test files related to a source file."""
+ test_patterns = [
+ # Jest/Vitest patterns
+ source_path.parent / f"{source_path.stem}.test{source_path.suffix}",
+ source_path.parent / f"{source_path.stem}.spec{source_path.suffix}",
+ source_path.parent / "__tests__" / f"{source_path.name}",
+ # Python patterns
+ source_path.parent / f"test_{source_path.stem}.py",
+ source_path.parent / f"{source_path.stem}_test.py",
+ # Go patterns
+ source_path.parent / f"{source_path.stem}_test.go",
+ ]
+
+ found = set()
+ for test_path in test_patterns:
+ full_path = self.project_dir / test_path
+ if full_path.exists() and full_path.is_file():
+ found.add(str(test_path))
+
+ return found
+
+ def _find_imports(self, content: str, source_path: Path) -> set[str]:
+ """
+ Find imported files from source code.
+
+ Supports:
+ - JavaScript/TypeScript: import statements
+ - Python: import statements
+ """
+ imports = set()
+
+ if source_path.suffix in [".ts", ".tsx", ".js", ".jsx"]:
+ # Match: import ... from './file' or from '../file'
+ # Only relative imports (starting with . or ..)
+ pattern = r"from\s+['\"](\.[^'\"]+)['\"]"
+ for match in re.finditer(pattern, content):
+ import_path = match.group(1)
+ resolved = self._resolve_import_path(import_path, source_path)
+ if resolved:
+ imports.add(resolved)
+
+ elif source_path.suffix == ".py":
+ # Python relative imports are complex, skip for now
+ # Could add support for "from . import" later
+ pass
+
+ return imports
+
+ def _resolve_import_path(self, import_path: str, source_path: Path) -> str | None:
+ """
+ Resolve a relative import path to an absolute file path.
+
+ Args:
+ import_path: Relative import like './utils' or '../config'
+ source_path: Path of the file doing the importing
+
+ Returns:
+ Absolute path relative to project root, or None if not found
+ """
+ # Start from the directory containing the source file
+ base_dir = source_path.parent
+
+ # Resolve relative path
+ resolved = (base_dir / import_path).resolve()
+
+ # Try common extensions if no extension provided
+ if not resolved.suffix:
+ for ext in [".ts", ".tsx", ".js", ".jsx"]:
+ candidate = resolved.with_suffix(ext)
+ if candidate.exists() and candidate.is_file():
+ try:
+ rel_path = candidate.relative_to(self.project_dir)
+ return str(rel_path)
+ except ValueError:
+ # File is outside project directory
+ return None
+
+ # Also check for index files
+ for ext in [".ts", ".tsx", ".js", ".jsx"]:
+ index_file = resolved / f"index{ext}"
+ if index_file.exists() and index_file.is_file():
+ try:
+ rel_path = index_file.relative_to(self.project_dir)
+ return str(rel_path)
+ except ValueError:
+ return None
+
+ # File with extension
+ if resolved.exists() and resolved.is_file():
+ try:
+ rel_path = resolved.relative_to(self.project_dir)
+ return str(rel_path)
+ except ValueError:
+ return None
+
+ return None
+
+ def _find_config_files(self, directory: Path) -> set[str]:
+ """Find configuration files in a directory."""
+ config_names = [
+ "tsconfig.json",
+ "package.json",
+ "pyproject.toml",
+ "setup.py",
+ ".eslintrc",
+ ".prettierrc",
+ "jest.config.js",
+ "vitest.config.ts",
+ "vite.config.ts",
+ ]
+
+ found = set()
+ for name in config_names:
+ config_path = directory / name
+ full_path = self.project_dir / config_path
+ if full_path.exists() and full_path.is_file():
+ found.add(str(config_path))
+
+ return found
+
+ def _find_type_definitions(self, source_path: Path) -> set[str]:
+ """Find TypeScript type definition files."""
+ # Look for .d.ts files with same name
+ type_def = source_path.parent / f"{source_path.stem}.d.ts"
+ full_path = self.project_dir / type_def
+
+ if full_path.exists() and full_path.is_file():
+ return {str(type_def)}
+
+ return set()
+
+
+class FollowupContextGatherer:
+ """
+ Gathers context specifically for follow-up reviews.
+
+ Unlike the full PRContextGatherer, this only fetches:
+ - New commits since last review
+ - Changed files since last review
+ - New comments since last review
+ """
+
+ def __init__(
+ self,
+ project_dir: Path,
+ pr_number: int,
+ previous_review: PRReviewResult, # Forward reference
+ ):
+ self.project_dir = Path(project_dir)
+ self.pr_number = pr_number
+ self.previous_review = previous_review
+ self.gh_client = GHClient(
+ project_dir=self.project_dir,
+ default_timeout=30.0,
+ max_retries=3,
+ )
+
+ async def gather(self) -> FollowupReviewContext:
+ """
+ Gather context for a follow-up review.
+
+ Returns:
+ FollowupReviewContext with changes since last review
+ """
+ # Import here to avoid circular imports
+ try:
+ from .models import FollowupReviewContext
+ except (ImportError, ValueError, SystemError):
+ from models import FollowupReviewContext
+
+ previous_sha = self.previous_review.reviewed_commit_sha
+
+ if not previous_sha:
+ print(
+ "[Followup] No reviewed_commit_sha in previous review, cannot gather incremental context",
+ flush=True,
+ )
+ return FollowupReviewContext(
+ pr_number=self.pr_number,
+ previous_review=self.previous_review,
+ previous_commit_sha="",
+ current_commit_sha="",
+ )
+
+ print(
+ f"[Followup] Gathering context since commit {previous_sha[:8]}...",
+ flush=True,
+ )
+
+ # Get current HEAD SHA
+ current_sha = await self.gh_client.get_pr_head_sha(self.pr_number)
+
+ if not current_sha:
+ print("[Followup] Could not fetch current HEAD SHA", flush=True)
+ return FollowupReviewContext(
+ pr_number=self.pr_number,
+ previous_review=self.previous_review,
+ previous_commit_sha=previous_sha,
+ current_commit_sha="",
+ )
+
+ if previous_sha == current_sha:
+ print("[Followup] No new commits since last review", flush=True)
+ return FollowupReviewContext(
+ pr_number=self.pr_number,
+ previous_review=self.previous_review,
+ previous_commit_sha=previous_sha,
+ current_commit_sha=current_sha,
+ )
+
+ print(
+ f"[Followup] Comparing {previous_sha[:8]}...{current_sha[:8]}", flush=True
+ )
+
+ # Get commit comparison
+ try:
+ comparison = await self.gh_client.compare_commits(previous_sha, current_sha)
+ except Exception as e:
+ print(f"[Followup] Error comparing commits: {e}", flush=True)
+ return FollowupReviewContext(
+ pr_number=self.pr_number,
+ previous_review=self.previous_review,
+ previous_commit_sha=previous_sha,
+ current_commit_sha=current_sha,
+ )
+
+ # Extract data from comparison
+ commits = comparison.get("commits", [])
+ files = comparison.get("files", [])
+ print(
+ f"[Followup] Found {len(commits)} new commits, {len(files)} changed files",
+ flush=True,
+ )
+
+ # Build diff from file patches
+ diff_parts = []
+ files_changed = []
+ for file_info in files:
+ filename = file_info.get("filename", "")
+ files_changed.append(filename)
+ patch = file_info.get("patch", "")
+ if patch:
+ diff_parts.append(f"--- a/{filename}\n+++ b/{filename}\n{patch}")
+
+ diff_since_review = "\n\n".join(diff_parts)
+
+ # Get comments since last review
+ try:
+ comments = await self.gh_client.get_comments_since(
+ self.pr_number, self.previous_review.reviewed_at
+ )
+ except Exception as e:
+ print(f"[Followup] Error fetching comments: {e}", flush=True)
+ comments = {"review_comments": [], "issue_comments": []}
+
+ # Separate AI bot comments from contributor comments
+ ai_comments = []
+ contributor_comments = []
+
+ all_comments = comments.get("review_comments", []) + comments.get(
+ "issue_comments", []
+ )
+
+ for comment in all_comments:
+ author = ""
+ if isinstance(comment.get("user"), dict):
+ author = comment["user"].get("login", "").lower()
+ elif isinstance(comment.get("author"), dict):
+ author = comment["author"].get("login", "").lower()
+
+ is_ai_bot = any(pattern in author for pattern in AI_BOT_PATTERNS.keys())
+
+ if is_ai_bot:
+ ai_comments.append(comment)
+ else:
+ contributor_comments.append(comment)
+
+ print(
+ f"[Followup] Found {len(contributor_comments)} contributor comments, {len(ai_comments)} AI comments",
+ flush=True,
+ )
+
+ return FollowupReviewContext(
+ pr_number=self.pr_number,
+ previous_review=self.previous_review,
+ previous_commit_sha=previous_sha,
+ current_commit_sha=current_sha,
+ commits_since_review=commits,
+ files_changed_since_review=files_changed,
+ diff_since_review=diff_since_review,
+ contributor_comments_since_review=contributor_comments,
+ ai_bot_comments_since_review=ai_comments,
+ )
diff --git a/apps/backend/runners/github/duplicates.py b/apps/backend/runners/github/duplicates.py
new file mode 100644
index 00000000..47d3dce4
--- /dev/null
+++ b/apps/backend/runners/github/duplicates.py
@@ -0,0 +1,601 @@
+"""
+Semantic Duplicate Detection
+============================
+
+Uses embeddings-based similarity to detect duplicate issues:
+- Replaces simple word overlap with semantic similarity
+- Integrates with OpenAI/Voyage AI embeddings
+- Caches embeddings with TTL
+- Extracts entities (error codes, file paths, function names)
+- Provides similarity breakdown by component
+"""
+
+from __future__ import annotations
+
+import hashlib
+import json
+import logging
+import re
+from dataclasses import dataclass, field
+from datetime import datetime, timedelta, timezone
+from pathlib import Path
+from typing import Any
+
+logger = logging.getLogger(__name__)
+
+# Thresholds for duplicate detection
+DUPLICATE_THRESHOLD = 0.85 # Cosine similarity for "definitely duplicate"
+SIMILAR_THRESHOLD = 0.70 # Cosine similarity for "potentially related"
+EMBEDDING_CACHE_TTL_HOURS = 24
+
+
+@dataclass
+class EntityExtraction:
+ """Extracted entities from issue content."""
+
+ error_codes: list[str] = field(default_factory=list)
+ file_paths: list[str] = field(default_factory=list)
+ function_names: list[str] = field(default_factory=list)
+ urls: list[str] = field(default_factory=list)
+ stack_traces: list[str] = field(default_factory=list)
+ versions: list[str] = field(default_factory=list)
+
+ def to_dict(self) -> dict[str, list[str]]:
+ return {
+ "error_codes": self.error_codes,
+ "file_paths": self.file_paths,
+ "function_names": self.function_names,
+ "urls": self.urls,
+ "stack_traces": self.stack_traces,
+ "versions": self.versions,
+ }
+
+ def overlap_with(self, other: EntityExtraction) -> dict[str, float]:
+ """Calculate overlap with another extraction."""
+
+ def jaccard(a: list, b: list) -> float:
+ if not a and not b:
+ return 0.0
+ set_a, set_b = set(a), set(b)
+ intersection = len(set_a & set_b)
+ union = len(set_a | set_b)
+ return intersection / union if union > 0 else 0.0
+
+ return {
+ "error_codes": jaccard(self.error_codes, other.error_codes),
+ "file_paths": jaccard(self.file_paths, other.file_paths),
+ "function_names": jaccard(self.function_names, other.function_names),
+ "urls": jaccard(self.urls, other.urls),
+ }
+
+
+@dataclass
+class SimilarityResult:
+ """Result of similarity comparison between two issues."""
+
+ issue_a: int
+ issue_b: int
+ overall_score: float
+ title_score: float
+ body_score: float
+ entity_scores: dict[str, float]
+ is_duplicate: bool
+ is_similar: bool
+ explanation: str
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "issue_a": self.issue_a,
+ "issue_b": self.issue_b,
+ "overall_score": self.overall_score,
+ "title_score": self.title_score,
+ "body_score": self.body_score,
+ "entity_scores": self.entity_scores,
+ "is_duplicate": self.is_duplicate,
+ "is_similar": self.is_similar,
+ "explanation": self.explanation,
+ }
+
+
+@dataclass
+class CachedEmbedding:
+ """Cached embedding with metadata."""
+
+ issue_number: int
+ content_hash: str
+ embedding: list[float]
+ created_at: str
+ expires_at: str
+
+ def is_expired(self) -> bool:
+ expires = datetime.fromisoformat(self.expires_at)
+ return datetime.now(timezone.utc) > expires
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "issue_number": self.issue_number,
+ "content_hash": self.content_hash,
+ "embedding": self.embedding,
+ "created_at": self.created_at,
+ "expires_at": self.expires_at,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict[str, Any]) -> CachedEmbedding:
+ return cls(**data)
+
+
+class EntityExtractor:
+ """Extracts entities from issue content."""
+
+ # Patterns for entity extraction
+ ERROR_CODE_PATTERN = re.compile(
+ r"\b(?:E|ERR|ERROR|WARN|WARNING|FATAL)[-_]?\d{3,5}\b"
+ r"|\b[A-Z]{2,5}[-_]\d{3,5}\b"
+ r"|\bError\s*:\s*[A-Z_]+\b",
+ re.IGNORECASE,
+ )
+
+ FILE_PATH_PATTERN = re.compile(
+ r"(?:^|\s|[\"'`])([a-zA-Z0-9_./\\-]+\.[a-zA-Z]{1,5})(?:\s|[\"'`]|$|:|\()"
+ r"|(?:at\s+)([a-zA-Z0-9_./\\-]+\.[a-zA-Z]{1,5})(?::\d+)?",
+ re.MULTILINE,
+ )
+
+ FUNCTION_NAME_PATTERN = re.compile(
+ r"\b([a-zA-Z_][a-zA-Z0-9_]*)\s*\("
+ r"|\bfunction\s+([a-zA-Z_][a-zA-Z0-9_]*)"
+ r"|\bdef\s+([a-zA-Z_][a-zA-Z0-9_]*)"
+ r"|\basync\s+(?:function\s+)?([a-zA-Z_][a-zA-Z0-9_]*)",
+ )
+
+ URL_PATTERN = re.compile(
+ r"https?://[^\s<>\"')\]]+",
+ re.IGNORECASE,
+ )
+
+ VERSION_PATTERN = re.compile(
+ r"\bv?\d+\.\d+(?:\.\d+)?(?:-[a-zA-Z0-9.]+)?\b",
+ )
+
+ STACK_TRACE_PATTERN = re.compile(
+ r"(?:at\s+[^\n]+\n)+|(?:File\s+\"[^\"]+\",\s+line\s+\d+)",
+ re.MULTILINE,
+ )
+
+ def extract(self, content: str) -> EntityExtraction:
+ """Extract entities from content."""
+ extraction = EntityExtraction()
+
+ # Extract error codes
+ extraction.error_codes = list(set(self.ERROR_CODE_PATTERN.findall(content)))
+
+ # Extract file paths
+ path_matches = self.FILE_PATH_PATTERN.findall(content)
+ paths = []
+ for match in path_matches:
+ path = match[0] or match[1]
+ if path and len(path) > 3: # Filter out short false positives
+ paths.append(path)
+ extraction.file_paths = list(set(paths))
+
+ # Extract function names
+ func_matches = self.FUNCTION_NAME_PATTERN.findall(content)
+ funcs = []
+ for match in func_matches:
+ func = next((m for m in match if m), None)
+ if func and len(func) > 2:
+ funcs.append(func)
+ extraction.function_names = list(set(funcs))[:20] # Limit
+
+ # Extract URLs
+ extraction.urls = list(set(self.URL_PATTERN.findall(content)))[:10]
+
+ # Extract versions
+ extraction.versions = list(set(self.VERSION_PATTERN.findall(content)))[:10]
+
+ # Extract stack traces (simplified)
+ traces = self.STACK_TRACE_PATTERN.findall(content)
+ extraction.stack_traces = traces[:3] # Keep first 3
+
+ return extraction
+
+
+class EmbeddingProvider:
+ """
+ Abstract embedding provider.
+
+ Supports multiple backends:
+ - OpenAI (text-embedding-3-small)
+ - Voyage AI (voyage-large-2)
+ - Local (sentence-transformers)
+ """
+
+ def __init__(
+ self,
+ provider: str = "openai",
+ api_key: str | None = None,
+ model: str | None = None,
+ ):
+ self.provider = provider
+ self.api_key = api_key
+ self.model = model or self._default_model()
+
+ def _default_model(self) -> str:
+ defaults = {
+ "openai": "text-embedding-3-small",
+ "voyage": "voyage-large-2",
+ "local": "all-MiniLM-L6-v2",
+ }
+ return defaults.get(self.provider, "text-embedding-3-small")
+
+ async def get_embedding(self, text: str) -> list[float]:
+ """Get embedding for text."""
+ if self.provider == "openai":
+ return await self._openai_embedding(text)
+ elif self.provider == "voyage":
+ return await self._voyage_embedding(text)
+ else:
+ return await self._local_embedding(text)
+
+ async def _openai_embedding(self, text: str) -> list[float]:
+ """Get embedding from OpenAI."""
+ try:
+ import openai
+
+ client = openai.AsyncOpenAI(api_key=self.api_key)
+ response = await client.embeddings.create(
+ model=self.model,
+ input=text[:8000], # Limit input
+ )
+ return response.data[0].embedding
+ except Exception as e:
+ logger.error(f"OpenAI embedding error: {e}")
+ raise Exception(
+ f"OpenAI embeddings required but failed: {e}. Configure OPENAI_API_KEY or use 'local' provider."
+ )
+
+ async def _voyage_embedding(self, text: str) -> list[float]:
+ """Get embedding from Voyage AI."""
+ try:
+ import httpx
+
+ async with httpx.AsyncClient() as client:
+ response = await client.post(
+ "https://api.voyageai.com/v1/embeddings",
+ headers={"Authorization": f"Bearer {self.api_key}"},
+ json={
+ "model": self.model,
+ "input": text[:8000],
+ },
+ )
+ data = response.json()
+ return data["data"][0]["embedding"]
+ except Exception as e:
+ logger.error(f"Voyage embedding error: {e}")
+ raise Exception(
+ f"Voyage embeddings required but failed: {e}. Configure VOYAGE_API_KEY or use 'local' provider."
+ )
+
+ async def _local_embedding(self, text: str) -> list[float]:
+ """Get embedding from local model."""
+ try:
+ from sentence_transformers import SentenceTransformer
+
+ model = SentenceTransformer(self.model)
+ embedding = model.encode(text[:8000])
+ return embedding.tolist()
+ except Exception as e:
+ logger.error(f"Local embedding error: {e}")
+ raise Exception(
+ f"Local embeddings required but failed: {e}. Install sentence-transformers: pip install sentence-transformers"
+ )
+
+
+class DuplicateDetector:
+ """
+ Semantic duplicate detection for GitHub issues.
+
+ Usage:
+ detector = DuplicateDetector(
+ cache_dir=Path(".auto-claude/github/embeddings"),
+ embedding_provider="openai",
+ )
+
+ # Check for duplicates
+ duplicates = await detector.find_duplicates(
+ issue_number=123,
+ title="Login fails with OAuth",
+ body="When trying to login...",
+ open_issues=all_issues,
+ )
+ """
+
+ def __init__(
+ self,
+ cache_dir: Path,
+ embedding_provider: str = "openai",
+ api_key: str | None = None,
+ duplicate_threshold: float = DUPLICATE_THRESHOLD,
+ similar_threshold: float = SIMILAR_THRESHOLD,
+ cache_ttl_hours: int = EMBEDDING_CACHE_TTL_HOURS,
+ ):
+ self.cache_dir = cache_dir
+ self.cache_dir.mkdir(parents=True, exist_ok=True)
+ self.duplicate_threshold = duplicate_threshold
+ self.similar_threshold = similar_threshold
+ self.cache_ttl_hours = cache_ttl_hours
+
+ self.embedding_provider = EmbeddingProvider(
+ provider=embedding_provider,
+ api_key=api_key,
+ )
+ self.entity_extractor = EntityExtractor()
+
+ def _get_cache_file(self, repo: str) -> Path:
+ safe_name = repo.replace("/", "_")
+ return self.cache_dir / f"{safe_name}_embeddings.json"
+
+ def _content_hash(self, title: str, body: str) -> str:
+ """Generate hash of issue content."""
+ content = f"{title}\n{body}"
+ return hashlib.sha256(content.encode()).hexdigest()[:16]
+
+ def _load_cache(self, repo: str) -> dict[int, CachedEmbedding]:
+ """Load embedding cache for a repo."""
+ cache_file = self._get_cache_file(repo)
+ if not cache_file.exists():
+ return {}
+
+ with open(cache_file) as f:
+ data = json.load(f)
+
+ cache = {}
+ for item in data.get("embeddings", []):
+ embedding = CachedEmbedding.from_dict(item)
+ if not embedding.is_expired():
+ cache[embedding.issue_number] = embedding
+
+ return cache
+
+ def _save_cache(self, repo: str, cache: dict[int, CachedEmbedding]) -> None:
+ """Save embedding cache for a repo."""
+ cache_file = self._get_cache_file(repo)
+ data = {
+ "embeddings": [e.to_dict() for e in cache.values()],
+ "last_updated": datetime.now(timezone.utc).isoformat(),
+ }
+ with open(cache_file, "w") as f:
+ json.dump(data, f)
+
+ async def get_embedding(
+ self,
+ repo: str,
+ issue_number: int,
+ title: str,
+ body: str,
+ ) -> list[float]:
+ """Get embedding for an issue, using cache if available."""
+ cache = self._load_cache(repo)
+ content_hash = self._content_hash(title, body)
+
+ # Check cache
+ if issue_number in cache:
+ cached = cache[issue_number]
+ if cached.content_hash == content_hash and not cached.is_expired():
+ return cached.embedding
+
+ # Generate new embedding
+ content = f"{title}\n\n{body}"
+ embedding = await self.embedding_provider.get_embedding(content)
+
+ # Cache it
+ now = datetime.now(timezone.utc)
+ cache[issue_number] = CachedEmbedding(
+ issue_number=issue_number,
+ content_hash=content_hash,
+ embedding=embedding,
+ created_at=now.isoformat(),
+ expires_at=(now + timedelta(hours=self.cache_ttl_hours)).isoformat(),
+ )
+ self._save_cache(repo, cache)
+
+ return embedding
+
+ def cosine_similarity(self, a: list[float], b: list[float]) -> float:
+ """Calculate cosine similarity between two embeddings."""
+ if len(a) != len(b):
+ return 0.0
+
+ dot_product = sum(x * y for x, y in zip(a, b))
+ magnitude_a = sum(x * x for x in a) ** 0.5
+ magnitude_b = sum(x * x for x in b) ** 0.5
+
+ if magnitude_a == 0 or magnitude_b == 0:
+ return 0.0
+
+ return dot_product / (magnitude_a * magnitude_b)
+
+ async def compare_issues(
+ self,
+ repo: str,
+ issue_a: dict[str, Any],
+ issue_b: dict[str, Any],
+ ) -> SimilarityResult:
+ """Compare two issues for similarity."""
+ # Get embeddings
+ embed_a = await self.get_embedding(
+ repo,
+ issue_a["number"],
+ issue_a.get("title", ""),
+ issue_a.get("body", ""),
+ )
+ embed_b = await self.get_embedding(
+ repo,
+ issue_b["number"],
+ issue_b.get("title", ""),
+ issue_b.get("body", ""),
+ )
+
+ # Calculate embedding similarity
+ overall_score = self.cosine_similarity(embed_a, embed_b)
+
+ # Get title-only embeddings
+ title_embed_a = await self.embedding_provider.get_embedding(
+ issue_a.get("title", "")
+ )
+ title_embed_b = await self.embedding_provider.get_embedding(
+ issue_b.get("title", "")
+ )
+ title_score = self.cosine_similarity(title_embed_a, title_embed_b)
+
+ # Get body-only score (if bodies exist)
+ body_a = issue_a.get("body", "")
+ body_b = issue_b.get("body", "")
+ if body_a and body_b:
+ body_embed_a = await self.embedding_provider.get_embedding(body_a)
+ body_embed_b = await self.embedding_provider.get_embedding(body_b)
+ body_score = self.cosine_similarity(body_embed_a, body_embed_b)
+ else:
+ body_score = 0.0
+
+ # Extract and compare entities
+ entities_a = self.entity_extractor.extract(
+ f"{issue_a.get('title', '')} {issue_a.get('body', '')}"
+ )
+ entities_b = self.entity_extractor.extract(
+ f"{issue_b.get('title', '')} {issue_b.get('body', '')}"
+ )
+ entity_scores = entities_a.overlap_with(entities_b)
+
+ # Determine duplicate/similar status
+ is_duplicate = overall_score >= self.duplicate_threshold
+ is_similar = overall_score >= self.similar_threshold
+
+ # Generate explanation
+ explanation = self._generate_explanation(
+ overall_score,
+ title_score,
+ body_score,
+ entity_scores,
+ is_duplicate,
+ )
+
+ return SimilarityResult(
+ issue_a=issue_a["number"],
+ issue_b=issue_b["number"],
+ overall_score=overall_score,
+ title_score=title_score,
+ body_score=body_score,
+ entity_scores=entity_scores,
+ is_duplicate=is_duplicate,
+ is_similar=is_similar,
+ explanation=explanation,
+ )
+
+ def _generate_explanation(
+ self,
+ overall: float,
+ title: float,
+ body: float,
+ entities: dict[str, float],
+ is_duplicate: bool,
+ ) -> str:
+ """Generate human-readable explanation of similarity."""
+ parts = []
+
+ if is_duplicate:
+ parts.append(f"High semantic similarity ({overall:.0%})")
+ else:
+ parts.append(f"Moderate similarity ({overall:.0%})")
+
+ parts.append(f"Title: {title:.0%}")
+ parts.append(f"Body: {body:.0%}")
+
+ # Highlight matching entities
+ for entity_type, score in entities.items():
+ if score > 0:
+ parts.append(f"{entity_type.replace('_', ' ').title()}: {score:.0%}")
+
+ return " | ".join(parts)
+
+ async def find_duplicates(
+ self,
+ repo: str,
+ issue_number: int,
+ title: str,
+ body: str,
+ open_issues: list[dict[str, Any]],
+ limit: int = 5,
+ ) -> list[SimilarityResult]:
+ """
+ Find potential duplicates for an issue.
+
+ Args:
+ repo: Repository in owner/repo format
+ issue_number: Issue to find duplicates for
+ title: Issue title
+ body: Issue body
+ open_issues: List of open issues to compare against
+ limit: Maximum duplicates to return
+
+ Returns:
+ List of SimilarityResult sorted by similarity
+ """
+ target_issue = {
+ "number": issue_number,
+ "title": title,
+ "body": body,
+ }
+
+ results = []
+ for issue in open_issues:
+ if issue.get("number") == issue_number:
+ continue
+
+ try:
+ result = await self.compare_issues(repo, target_issue, issue)
+ if result.is_similar:
+ results.append(result)
+ except Exception as e:
+ logger.error(f"Error comparing issues: {e}")
+
+ # Sort by overall score, descending
+ results.sort(key=lambda r: r.overall_score, reverse=True)
+ return results[:limit]
+
+ async def precompute_embeddings(
+ self,
+ repo: str,
+ issues: list[dict[str, Any]],
+ ) -> int:
+ """
+ Precompute embeddings for all issues.
+
+ Args:
+ repo: Repository
+ issues: List of issues
+
+ Returns:
+ Number of embeddings computed
+ """
+ count = 0
+ for issue in issues:
+ try:
+ await self.get_embedding(
+ repo,
+ issue["number"],
+ issue.get("title", ""),
+ issue.get("body", ""),
+ )
+ count += 1
+ except Exception as e:
+ logger.error(f"Error computing embedding for #{issue['number']}: {e}")
+
+ return count
+
+ def clear_cache(self, repo: str) -> None:
+ """Clear embedding cache for a repo."""
+ cache_file = self._get_cache_file(repo)
+ if cache_file.exists():
+ cache_file.unlink()
diff --git a/apps/backend/runners/github/errors.py b/apps/backend/runners/github/errors.py
new file mode 100644
index 00000000..f6cd044d
--- /dev/null
+++ b/apps/backend/runners/github/errors.py
@@ -0,0 +1,499 @@
+"""
+GitHub Automation Error Types
+=============================
+
+Structured error types for GitHub automation with:
+- Serializable error objects for IPC
+- Stack trace preservation
+- Error categorization for UI display
+- Actionable error messages with retry hints
+"""
+
+from __future__ import annotations
+
+import traceback
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from enum import Enum
+from typing import Any
+
+
+class ErrorCategory(str, Enum):
+ """Categories of errors for UI display and handling."""
+
+ # Authentication/Permission errors
+ AUTHENTICATION = "authentication"
+ PERMISSION = "permission"
+ TOKEN_EXPIRED = "token_expired"
+ INSUFFICIENT_SCOPE = "insufficient_scope"
+
+ # Rate limiting errors
+ RATE_LIMITED = "rate_limited"
+ COST_EXCEEDED = "cost_exceeded"
+
+ # Network/API errors
+ NETWORK = "network"
+ TIMEOUT = "timeout"
+ API_ERROR = "api_error"
+ SERVICE_UNAVAILABLE = "service_unavailable"
+
+ # Validation errors
+ VALIDATION = "validation"
+ INVALID_INPUT = "invalid_input"
+ NOT_FOUND = "not_found"
+
+ # State errors
+ INVALID_STATE = "invalid_state"
+ CONFLICT = "conflict"
+ ALREADY_EXISTS = "already_exists"
+
+ # Internal errors
+ INTERNAL = "internal"
+ CONFIGURATION = "configuration"
+
+ # Bot/Automation errors
+ BOT_DETECTED = "bot_detected"
+ CANCELLED = "cancelled"
+
+
+class ErrorSeverity(str, Enum):
+ """Severity levels for errors."""
+
+ INFO = "info" # Informational, not really an error
+ WARNING = "warning" # Something went wrong but recoverable
+ ERROR = "error" # Operation failed
+ CRITICAL = "critical" # System-level failure
+
+
+@dataclass
+class StructuredError:
+ """
+ Structured error object for IPC and UI display.
+
+ This class provides:
+ - Serialization for sending errors to frontend
+ - Stack trace preservation
+ - Actionable messages and retry hints
+ - Error categorization
+ """
+
+ # Core error info
+ message: str
+ category: ErrorCategory
+ severity: ErrorSeverity = ErrorSeverity.ERROR
+
+ # Context
+ code: str | None = None # Machine-readable error code
+ correlation_id: str | None = None
+ timestamp: str = field(
+ default_factory=lambda: datetime.now(timezone.utc).isoformat()
+ )
+
+ # Details
+ details: dict[str, Any] = field(default_factory=dict)
+ stack_trace: str | None = None
+
+ # Recovery hints
+ retryable: bool = False
+ retry_after_seconds: int | None = None
+ action_hint: str | None = None # e.g., "Click retry to attempt again"
+ help_url: str | None = None
+
+ # Source info
+ source: str | None = None # e.g., "orchestrator.review_pr"
+ pr_number: int | None = None
+ issue_number: int | None = None
+ repo: str | None = None
+
+ def to_dict(self) -> dict[str, Any]:
+ """Convert to dictionary for JSON serialization."""
+ return {
+ "message": self.message,
+ "category": self.category.value,
+ "severity": self.severity.value,
+ "code": self.code,
+ "correlation_id": self.correlation_id,
+ "timestamp": self.timestamp,
+ "details": self.details,
+ "stack_trace": self.stack_trace,
+ "retryable": self.retryable,
+ "retry_after_seconds": self.retry_after_seconds,
+ "action_hint": self.action_hint,
+ "help_url": self.help_url,
+ "source": self.source,
+ "pr_number": self.pr_number,
+ "issue_number": self.issue_number,
+ "repo": self.repo,
+ }
+
+ @classmethod
+ def from_exception(
+ cls,
+ exc: Exception,
+ category: ErrorCategory = ErrorCategory.INTERNAL,
+ severity: ErrorSeverity = ErrorSeverity.ERROR,
+ correlation_id: str | None = None,
+ **kwargs,
+ ) -> StructuredError:
+ """Create a StructuredError from an exception."""
+ return cls(
+ message=str(exc),
+ category=category,
+ severity=severity,
+ correlation_id=correlation_id,
+ stack_trace=traceback.format_exc(),
+ code=exc.__class__.__name__,
+ **kwargs,
+ )
+
+
+# Custom Exception Classes with structured error support
+
+
+class GitHubAutomationError(Exception):
+ """Base exception for GitHub automation errors."""
+
+ category: ErrorCategory = ErrorCategory.INTERNAL
+ severity: ErrorSeverity = ErrorSeverity.ERROR
+ retryable: bool = False
+ action_hint: str | None = None
+
+ def __init__(
+ self,
+ message: str,
+ details: dict[str, Any] | None = None,
+ correlation_id: str | None = None,
+ **kwargs,
+ ):
+ super().__init__(message)
+ self.message = message
+ self.details = details or {}
+ self.correlation_id = correlation_id
+ self.extra = kwargs
+
+ def to_structured_error(self) -> StructuredError:
+ """Convert to StructuredError for IPC."""
+ return StructuredError(
+ message=self.message,
+ category=self.category,
+ severity=self.severity,
+ code=self.__class__.__name__,
+ correlation_id=self.correlation_id,
+ details=self.details,
+ stack_trace=traceback.format_exc(),
+ retryable=self.retryable,
+ action_hint=self.action_hint,
+ **self.extra,
+ )
+
+
+class AuthenticationError(GitHubAutomationError):
+ """Authentication failed."""
+
+ category = ErrorCategory.AUTHENTICATION
+ action_hint = "Check your GitHub token configuration"
+
+
+class PermissionDeniedError(GitHubAutomationError):
+ """Permission denied for the operation."""
+
+ category = ErrorCategory.PERMISSION
+ action_hint = "Ensure you have the required permissions"
+
+
+class TokenExpiredError(GitHubAutomationError):
+ """GitHub token has expired."""
+
+ category = ErrorCategory.TOKEN_EXPIRED
+ action_hint = "Regenerate your GitHub token"
+
+
+class InsufficientScopeError(GitHubAutomationError):
+ """Token lacks required scopes."""
+
+ category = ErrorCategory.INSUFFICIENT_SCOPE
+ action_hint = "Regenerate token with required scopes: repo, read:org"
+
+
+class RateLimitError(GitHubAutomationError):
+ """Rate limit exceeded."""
+
+ category = ErrorCategory.RATE_LIMITED
+ severity = ErrorSeverity.WARNING
+ retryable = True
+
+ def __init__(
+ self,
+ message: str,
+ retry_after_seconds: int = 60,
+ **kwargs,
+ ):
+ super().__init__(message, **kwargs)
+ self.retry_after_seconds = retry_after_seconds
+ self.action_hint = f"Rate limited. Retry in {retry_after_seconds} seconds"
+
+ def to_structured_error(self) -> StructuredError:
+ error = super().to_structured_error()
+ error.retry_after_seconds = self.retry_after_seconds
+ return error
+
+
+class CostLimitError(GitHubAutomationError):
+ """AI cost limit exceeded."""
+
+ category = ErrorCategory.COST_EXCEEDED
+ action_hint = "Increase cost limit in settings or wait until reset"
+
+
+class NetworkError(GitHubAutomationError):
+ """Network connection error."""
+
+ category = ErrorCategory.NETWORK
+ retryable = True
+ action_hint = "Check your internet connection and retry"
+
+
+class TimeoutError(GitHubAutomationError):
+ """Operation timed out."""
+
+ category = ErrorCategory.TIMEOUT
+ retryable = True
+ action_hint = "The operation took too long. Try again"
+
+
+class APIError(GitHubAutomationError):
+ """GitHub API returned an error."""
+
+ category = ErrorCategory.API_ERROR
+
+ def __init__(
+ self,
+ message: str,
+ status_code: int | None = None,
+ **kwargs,
+ ):
+ super().__init__(message, **kwargs)
+ self.status_code = status_code
+ self.details["status_code"] = status_code
+
+ # Set retryable based on status code
+ if status_code and status_code >= 500:
+ self.retryable = True
+ self.action_hint = "GitHub service issue. Retry later"
+
+
+class ServiceUnavailableError(GitHubAutomationError):
+ """Service temporarily unavailable."""
+
+ category = ErrorCategory.SERVICE_UNAVAILABLE
+ retryable = True
+ action_hint = "Service temporarily unavailable. Retry in a few minutes"
+
+
+class ValidationError(GitHubAutomationError):
+ """Input validation failed."""
+
+ category = ErrorCategory.VALIDATION
+
+
+class InvalidInputError(GitHubAutomationError):
+ """Invalid input provided."""
+
+ category = ErrorCategory.INVALID_INPUT
+
+
+class NotFoundError(GitHubAutomationError):
+ """Resource not found."""
+
+ category = ErrorCategory.NOT_FOUND
+
+
+class InvalidStateError(GitHubAutomationError):
+ """Invalid state transition attempted."""
+
+ category = ErrorCategory.INVALID_STATE
+
+
+class ConflictError(GitHubAutomationError):
+ """Conflicting operation detected."""
+
+ category = ErrorCategory.CONFLICT
+ action_hint = "Another operation is in progress. Wait and retry"
+
+
+class AlreadyExistsError(GitHubAutomationError):
+ """Resource already exists."""
+
+ category = ErrorCategory.ALREADY_EXISTS
+
+
+class BotDetectedError(GitHubAutomationError):
+ """Bot activity detected, skipping to prevent loops."""
+
+ category = ErrorCategory.BOT_DETECTED
+ severity = ErrorSeverity.INFO
+ action_hint = "Skipped to prevent infinite bot loops"
+
+
+class CancelledError(GitHubAutomationError):
+ """Operation was cancelled by user."""
+
+ category = ErrorCategory.CANCELLED
+ severity = ErrorSeverity.INFO
+
+
+class ConfigurationError(GitHubAutomationError):
+ """Configuration error."""
+
+ category = ErrorCategory.CONFIGURATION
+ action_hint = "Check your configuration settings"
+
+
+# Error handling utilities
+
+
+def capture_error(
+ exc: Exception,
+ correlation_id: str | None = None,
+ source: str | None = None,
+ pr_number: int | None = None,
+ issue_number: int | None = None,
+ repo: str | None = None,
+) -> StructuredError:
+ """
+ Capture any exception as a StructuredError.
+
+ Handles both GitHubAutomationError subclasses and generic exceptions.
+ """
+ if isinstance(exc, GitHubAutomationError):
+ error = exc.to_structured_error()
+ error.source = source
+ error.pr_number = pr_number
+ error.issue_number = issue_number
+ error.repo = repo
+ if correlation_id:
+ error.correlation_id = correlation_id
+ return error
+
+ # Map known exception types to categories
+ category = ErrorCategory.INTERNAL
+ retryable = False
+
+ if isinstance(exc, TimeoutError):
+ category = ErrorCategory.TIMEOUT
+ retryable = True
+ elif isinstance(exc, ConnectionError):
+ category = ErrorCategory.NETWORK
+ retryable = True
+ elif isinstance(exc, PermissionError):
+ category = ErrorCategory.PERMISSION
+ elif isinstance(exc, FileNotFoundError):
+ category = ErrorCategory.NOT_FOUND
+ elif isinstance(exc, ValueError):
+ category = ErrorCategory.VALIDATION
+
+ return StructuredError.from_exception(
+ exc,
+ category=category,
+ correlation_id=correlation_id,
+ source=source,
+ pr_number=pr_number,
+ issue_number=issue_number,
+ repo=repo,
+ retryable=retryable,
+ )
+
+
+def format_error_for_ui(error: StructuredError) -> dict[str, Any]:
+ """
+ Format error for frontend UI display.
+
+ Returns a simplified structure optimized for UI rendering.
+ """
+ return {
+ "title": _get_error_title(error.category),
+ "message": error.message,
+ "severity": error.severity.value,
+ "retryable": error.retryable,
+ "retry_after": error.retry_after_seconds,
+ "action": error.action_hint,
+ "details": {
+ "code": error.code,
+ "correlation_id": error.correlation_id,
+ "timestamp": error.timestamp,
+ **error.details,
+ },
+ "expandable": {
+ "stack_trace": error.stack_trace,
+ "help_url": error.help_url,
+ },
+ }
+
+
+def _get_error_title(category: ErrorCategory) -> str:
+ """Get human-readable title for error category."""
+ titles = {
+ ErrorCategory.AUTHENTICATION: "Authentication Failed",
+ ErrorCategory.PERMISSION: "Permission Denied",
+ ErrorCategory.TOKEN_EXPIRED: "Token Expired",
+ ErrorCategory.INSUFFICIENT_SCOPE: "Insufficient Permissions",
+ ErrorCategory.RATE_LIMITED: "Rate Limited",
+ ErrorCategory.COST_EXCEEDED: "Cost Limit Exceeded",
+ ErrorCategory.NETWORK: "Network Error",
+ ErrorCategory.TIMEOUT: "Operation Timed Out",
+ ErrorCategory.API_ERROR: "GitHub API Error",
+ ErrorCategory.SERVICE_UNAVAILABLE: "Service Unavailable",
+ ErrorCategory.VALIDATION: "Validation Error",
+ ErrorCategory.INVALID_INPUT: "Invalid Input",
+ ErrorCategory.NOT_FOUND: "Not Found",
+ ErrorCategory.INVALID_STATE: "Invalid State",
+ ErrorCategory.CONFLICT: "Conflict Detected",
+ ErrorCategory.ALREADY_EXISTS: "Already Exists",
+ ErrorCategory.INTERNAL: "Internal Error",
+ ErrorCategory.CONFIGURATION: "Configuration Error",
+ ErrorCategory.BOT_DETECTED: "Bot Activity Detected",
+ ErrorCategory.CANCELLED: "Operation Cancelled",
+ }
+ return titles.get(category, "Error")
+
+
+# Result type for operations that may fail
+
+
+@dataclass
+class Result:
+ """
+ Result type for operations that may succeed or fail.
+
+ Usage:
+ result = Result.success(data={"findings": [...]})
+ result = Result.failure(error=structured_error)
+
+ if result.ok:
+ process(result.data)
+ else:
+ handle_error(result.error)
+ """
+
+ ok: bool
+ data: dict[str, Any] | None = None
+ error: StructuredError | None = None
+
+ @classmethod
+ def success(cls, data: dict[str, Any] | None = None) -> Result:
+ return cls(ok=True, data=data)
+
+ @classmethod
+ def failure(cls, error: StructuredError) -> Result:
+ return cls(ok=False, error=error)
+
+ @classmethod
+ def from_exception(cls, exc: Exception, **kwargs) -> Result:
+ return cls.failure(capture_error(exc, **kwargs))
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "ok": self.ok,
+ "data": self.data,
+ "error": self.error.to_dict() if self.error else None,
+ }
diff --git a/apps/backend/runners/github/example_usage.py b/apps/backend/runners/github/example_usage.py
new file mode 100644
index 00000000..3deeb0ad
--- /dev/null
+++ b/apps/backend/runners/github/example_usage.py
@@ -0,0 +1,312 @@
+"""
+Example Usage of File Locking in GitHub Automation
+==================================================
+
+Demonstrates real-world usage patterns for the file locking system.
+"""
+
+import asyncio
+from pathlib import Path
+
+from models import (
+ AutoFixState,
+ AutoFixStatus,
+ PRReviewFinding,
+ PRReviewResult,
+ ReviewCategory,
+ ReviewSeverity,
+ TriageCategory,
+ TriageResult,
+)
+
+
+async def example_concurrent_auto_fix():
+ """
+ Example: Multiple auto-fix jobs running concurrently.
+
+ Scenario: 3 GitHub issues are being auto-fixed simultaneously.
+ Each job needs to:
+ 1. Save its state to disk
+ 2. Update the shared auto-fix queue index
+
+ Without file locking: Race conditions corrupt the index
+ With file locking: All updates are atomic and safe
+ """
+ print("\n=== Example 1: Concurrent Auto-Fix Jobs ===\n")
+
+ github_dir = Path(".auto-claude/github")
+
+ async def process_auto_fix(issue_number: int):
+ """Simulate an auto-fix job processing an issue."""
+ print(f"Job {issue_number}: Starting auto-fix...")
+
+ # Create auto-fix state
+ state = AutoFixState(
+ issue_number=issue_number,
+ issue_url=f"https://github.com/owner/repo/issues/{issue_number}",
+ repo="owner/repo",
+ status=AutoFixStatus.ANALYZING,
+ )
+
+ # Save state - uses locked_json_write internally
+ state.save(github_dir)
+ print(f"Job {issue_number}: State saved")
+
+ # Simulate work
+ await asyncio.sleep(0.1)
+
+ # Update status
+ state.update_status(AutoFixStatus.CREATING_SPEC)
+ state.spec_id = f"spec-{issue_number}"
+
+ # Save again - atomically updates both state file and index
+ state.save(github_dir)
+ print(f"Job {issue_number}: Updated to CREATING_SPEC")
+
+ # More work
+ await asyncio.sleep(0.1)
+
+ # Final update
+ state.update_status(AutoFixStatus.COMPLETED)
+ state.pr_number = 100 + issue_number
+ state.pr_url = f"https://github.com/owner/repo/pull/{state.pr_number}"
+
+ # Final save - all updates are atomic
+ state.save(github_dir)
+ print(f"Job {issue_number}: Completed successfully")
+
+ # Run 3 concurrent auto-fix jobs
+ print("Starting 3 concurrent auto-fix jobs...\n")
+ await asyncio.gather(
+ process_auto_fix(1001),
+ process_auto_fix(1002),
+ process_auto_fix(1003),
+ )
+
+ print("\n✓ All jobs completed without data corruption!")
+ print("✓ Index file contains all 3 auto-fix entries")
+
+
+async def example_concurrent_pr_reviews():
+ """
+ Example: Multiple PR reviews happening concurrently.
+
+ Scenario: CI/CD is reviewing multiple PRs in parallel.
+ Each review needs to:
+ 1. Save review results to disk
+ 2. Update the shared PR review index
+
+ File locking ensures no reviews are lost.
+ """
+ print("\n=== Example 2: Concurrent PR Reviews ===\n")
+
+ github_dir = Path(".auto-claude/github")
+
+ async def review_pr(pr_number: int, findings_count: int, status: str):
+ """Simulate reviewing a PR."""
+ print(f"Reviewing PR #{pr_number}...")
+
+ # Create findings
+ findings = [
+ PRReviewFinding(
+ id=f"finding-{i}",
+ severity=ReviewSeverity.MEDIUM,
+ category=ReviewCategory.QUALITY,
+ title=f"Finding {i}",
+ description=f"Issue found in PR #{pr_number}",
+ file="src/main.py",
+ line=10 + i,
+ fixable=True,
+ )
+ for i in range(findings_count)
+ ]
+
+ # Create review result
+ review = PRReviewResult(
+ pr_number=pr_number,
+ repo="owner/repo",
+ success=True,
+ findings=findings,
+ summary=f"Found {findings_count} issues in PR #{pr_number}",
+ overall_status=status,
+ )
+
+ # Save review - uses locked_json_write internally
+ review.save(github_dir)
+ print(f"PR #{pr_number}: Review saved with {findings_count} findings")
+
+ return review
+
+ # Review 5 PRs concurrently
+ print("Reviewing 5 PRs concurrently...\n")
+ reviews = await asyncio.gather(
+ review_pr(101, 3, "comment"),
+ review_pr(102, 5, "request_changes"),
+ review_pr(103, 0, "approve"),
+ review_pr(104, 2, "comment"),
+ review_pr(105, 1, "approve"),
+ )
+
+ print(f"\n✓ All {len(reviews)} reviews saved successfully!")
+ print("✓ Index file contains all review summaries")
+
+
+async def example_triage_queue():
+ """
+ Example: Issue triage with concurrent processing.
+
+ Scenario: Bot is triaging new issues as they come in.
+ Multiple issues can be triaged simultaneously.
+
+ File locking prevents duplicate triage or lost results.
+ """
+ print("\n=== Example 3: Concurrent Issue Triage ===\n")
+
+ github_dir = Path(".auto-claude/github")
+
+ async def triage_issue(issue_number: int, category: TriageCategory, priority: str):
+ """Simulate triaging an issue."""
+ print(f"Triaging issue #{issue_number}...")
+
+ # Create triage result
+ triage = TriageResult(
+ issue_number=issue_number,
+ repo="owner/repo",
+ category=category,
+ confidence=0.85,
+ labels_to_add=[category.value, priority],
+ priority=priority,
+ comment=f"Automatically triaged as {category.value}",
+ )
+
+ # Save triage result - uses locked_json_write internally
+ triage.save(github_dir)
+ print(f"Issue #{issue_number}: Triaged as {category.value} ({priority})")
+
+ return triage
+
+ # Triage multiple issues concurrently
+ print("Triaging 4 issues concurrently...\n")
+ triages = await asyncio.gather(
+ triage_issue(2001, TriageCategory.BUG, "high"),
+ triage_issue(2002, TriageCategory.FEATURE, "medium"),
+ triage_issue(2003, TriageCategory.DOCUMENTATION, "low"),
+ triage_issue(2004, TriageCategory.BUG, "critical"),
+ )
+
+ print(f"\n✓ All {len(triages)} issues triaged successfully!")
+ print("✓ No race conditions or lost triage results")
+
+
+async def example_index_collision():
+ """
+ Example: Demonstrating the index update collision problem.
+
+ This shows why file locking is critical for the index files.
+ Without locking, concurrent updates corrupt the index.
+ """
+ print("\n=== Example 4: Why Index Locking is Critical ===\n")
+
+ github_dir = Path(".auto-claude/github")
+
+ print("Scenario: 10 concurrent auto-fix jobs all updating the same index")
+ print("Without locking: Updates overwrite each other (lost updates)")
+ print("With locking: All 10 updates are applied correctly\n")
+
+ async def quick_update(issue_number: int):
+ """Quick auto-fix update."""
+ state = AutoFixState(
+ issue_number=issue_number,
+ issue_url=f"https://github.com/owner/repo/issues/{issue_number}",
+ repo="owner/repo",
+ status=AutoFixStatus.PENDING,
+ )
+ state.save(github_dir)
+
+ # Create 10 concurrent updates
+ print("Creating 10 concurrent auto-fix states...")
+ await asyncio.gather(*[quick_update(3000 + i) for i in range(10)])
+
+ print("\n✓ All 10 updates completed")
+ print("✓ Index contains all 10 entries (no lost updates)")
+ print("✓ This is only possible with proper file locking!")
+
+
+async def example_error_handling():
+ """
+ Example: Proper error handling with file locking.
+
+ Shows how to handle lock timeouts and other failures gracefully.
+ """
+ print("\n=== Example 5: Error Handling ===\n")
+
+ github_dir = Path(".auto-claude/github")
+
+ from file_lock import FileLockTimeout, locked_json_write
+
+ async def save_with_retry(filepath: Path, data: dict, max_retries: int = 3):
+ """Save with automatic retry on lock timeout."""
+ for attempt in range(max_retries):
+ try:
+ await locked_json_write(filepath, data, timeout=2.0)
+ print(f"✓ Save succeeded on attempt {attempt + 1}")
+ return True
+ except FileLockTimeout:
+ if attempt == max_retries - 1:
+ print(f"✗ Failed after {max_retries} attempts")
+ return False
+ print(f"⚠ Lock timeout on attempt {attempt + 1}, retrying...")
+ await asyncio.sleep(0.5)
+
+ return False
+
+ # Try to save with retry logic
+ test_file = github_dir / "test" / "example.json"
+ test_file.parent.mkdir(parents=True, exist_ok=True)
+
+ print("Attempting save with retry logic...\n")
+ success = await save_with_retry(test_file, {"test": "data"})
+
+ if success:
+ print("\n✓ Data saved successfully with retry logic")
+ else:
+ print("\n✗ Save failed even with retries")
+
+
+async def main():
+ """Run all examples."""
+ print("=" * 70)
+ print("File Locking Examples - Real-World Usage Patterns")
+ print("=" * 70)
+
+ examples = [
+ example_concurrent_auto_fix,
+ example_concurrent_pr_reviews,
+ example_triage_queue,
+ example_index_collision,
+ example_error_handling,
+ ]
+
+ for example in examples:
+ try:
+ await example()
+ await asyncio.sleep(0.5) # Brief pause between examples
+ except Exception as e:
+ print(f"✗ Example failed: {e}")
+ import traceback
+
+ traceback.print_exc()
+
+ print("\n" + "=" * 70)
+ print("All Examples Completed!")
+ print("=" * 70)
+ print("\nKey Takeaways:")
+ print("1. File locking prevents data corruption in concurrent scenarios")
+ print("2. All save() methods now use atomic locked writes")
+ print("3. Index updates are protected from race conditions")
+ print("4. Lock timeouts can be handled gracefully with retries")
+ print("5. The system scales safely to multiple concurrent operations")
+
+
+if __name__ == "__main__":
+ asyncio.run(main())
diff --git a/apps/backend/runners/github/file_lock.py b/apps/backend/runners/github/file_lock.py
new file mode 100644
index 00000000..4683d591
--- /dev/null
+++ b/apps/backend/runners/github/file_lock.py
@@ -0,0 +1,413 @@
+"""
+File Locking for Concurrent Operations
+======================================
+
+Thread-safe and process-safe file locking utilities for GitHub automation.
+Uses fcntl.flock() on Unix systems for proper cross-process locking.
+
+Example Usage:
+ # Simple file locking
+ async with FileLock("path/to/file.json", timeout=5.0):
+ # Do work with locked file
+ pass
+
+ # Atomic write with locking
+ async with locked_write("path/to/file.json", timeout=5.0) as f:
+ json.dump(data, f)
+"""
+
+from __future__ import annotations
+
+import asyncio
+import fcntl
+import json
+import os
+import tempfile
+import time
+from contextlib import asynccontextmanager, contextmanager
+from pathlib import Path
+from typing import Any
+
+
+class FileLockError(Exception):
+ """Raised when file locking operations fail."""
+
+ pass
+
+
+class FileLockTimeout(FileLockError):
+ """Raised when lock acquisition times out."""
+
+ pass
+
+
+class FileLock:
+ """
+ Cross-process file lock using fcntl.flock().
+
+ Supports both sync and async context managers for flexible usage.
+
+ Args:
+ filepath: Path to file to lock (will be created if needed)
+ timeout: Maximum seconds to wait for lock (default: 5.0)
+ exclusive: Whether to use exclusive lock (default: True)
+
+ Example:
+ # Synchronous usage
+ with FileLock("/path/to/file.json"):
+ # File is locked
+ pass
+
+ # Asynchronous usage
+ async with FileLock("/path/to/file.json"):
+ # File is locked
+ pass
+ """
+
+ def __init__(
+ self,
+ filepath: str | Path,
+ timeout: float = 5.0,
+ exclusive: bool = True,
+ ):
+ self.filepath = Path(filepath)
+ self.timeout = timeout
+ self.exclusive = exclusive
+ self._lock_file: Path | None = None
+ self._fd: int | None = None
+
+ def _get_lock_file(self) -> Path:
+ """Get lock file path (separate .lock file)."""
+ return self.filepath.parent / f"{self.filepath.name}.lock"
+
+ def _acquire_lock(self) -> None:
+ """Acquire the file lock (blocking with timeout)."""
+ self._lock_file = self._get_lock_file()
+ self._lock_file.parent.mkdir(parents=True, exist_ok=True)
+
+ # Open lock file
+ self._fd = os.open(str(self._lock_file), os.O_CREAT | os.O_RDWR)
+
+ # Try to acquire lock with timeout
+ lock_mode = fcntl.LOCK_EX if self.exclusive else fcntl.LOCK_SH
+ start_time = time.time()
+
+ while True:
+ try:
+ # Non-blocking lock attempt
+ fcntl.flock(self._fd, lock_mode | fcntl.LOCK_NB)
+ return # Lock acquired
+ except BlockingIOError:
+ # Lock held by another process
+ elapsed = time.time() - start_time
+ if elapsed >= self.timeout:
+ os.close(self._fd)
+ self._fd = None
+ raise FileLockTimeout(
+ f"Failed to acquire lock on {self.filepath} within {self.timeout}s"
+ )
+
+ # Wait a bit before retrying
+ time.sleep(0.01)
+
+ def _release_lock(self) -> None:
+ """Release the file lock."""
+ if self._fd is not None:
+ try:
+ fcntl.flock(self._fd, fcntl.LOCK_UN)
+ os.close(self._fd)
+ except Exception:
+ pass # Best effort cleanup
+ finally:
+ self._fd = None
+
+ # Clean up lock file
+ if self._lock_file and self._lock_file.exists():
+ try:
+ self._lock_file.unlink()
+ except Exception:
+ pass # Best effort cleanup
+
+ def __enter__(self):
+ """Synchronous context manager entry."""
+ self._acquire_lock()
+ return self
+
+ def __exit__(self, exc_type, exc_val, exc_tb):
+ """Synchronous context manager exit."""
+ self._release_lock()
+ return False
+
+ async def __aenter__(self):
+ """Async context manager entry."""
+ # Run blocking lock acquisition in thread pool
+ await asyncio.get_event_loop().run_in_executor(None, self._acquire_lock)
+ return self
+
+ async def __aexit__(self, exc_type, exc_val, exc_tb):
+ """Async context manager exit."""
+ await asyncio.get_event_loop().run_in_executor(None, self._release_lock)
+ return False
+
+
+@contextmanager
+def atomic_write(filepath: str | Path, mode: str = "w"):
+ """
+ Atomic file write using temp file and rename.
+
+ Writes to .tmp file first, then atomically replaces target file
+ using os.replace() which is atomic on POSIX systems.
+
+ Args:
+ filepath: Target file path
+ mode: File open mode (default: "w")
+
+ Example:
+ with atomic_write("/path/to/file.json") as f:
+ json.dump(data, f)
+ """
+ filepath = Path(filepath)
+ filepath.parent.mkdir(parents=True, exist_ok=True)
+
+ # Create temp file in same directory for atomic rename
+ fd, tmp_path = tempfile.mkstemp(
+ dir=filepath.parent, prefix=f".{filepath.name}.tmp.", suffix=""
+ )
+
+ try:
+ # Open temp file with requested mode
+ with os.fdopen(fd, mode) as f:
+ yield f
+
+ # Atomic replace - succeeds or fails completely
+ os.replace(tmp_path, filepath)
+
+ except Exception:
+ # Clean up temp file on error
+ try:
+ os.unlink(tmp_path)
+ except Exception:
+ pass
+ raise
+
+
+@asynccontextmanager
+async def locked_write(filepath: str | Path, timeout: float = 5.0, mode: str = "w"):
+ """
+ Async context manager combining file locking and atomic writes.
+
+ Acquires exclusive lock, writes to temp file, atomically replaces target.
+ This is the recommended way to safely write shared state files.
+
+ Args:
+ filepath: Target file path
+ timeout: Lock timeout in seconds (default: 5.0)
+ mode: File open mode (default: "w")
+
+ Example:
+ async with locked_write("/path/to/file.json", timeout=5.0) as f:
+ json.dump(data, f, indent=2)
+
+ Raises:
+ FileLockTimeout: If lock cannot be acquired within timeout
+ """
+ filepath = Path(filepath)
+
+ # Acquire lock
+ lock = FileLock(filepath, timeout=timeout, exclusive=True)
+ await lock.__aenter__()
+
+ try:
+ # Atomic write in thread pool (since it uses sync file I/O)
+ fd, tmp_path = await asyncio.get_event_loop().run_in_executor(
+ None,
+ lambda: tempfile.mkstemp(
+ dir=filepath.parent, prefix=f".{filepath.name}.tmp.", suffix=""
+ ),
+ )
+
+ try:
+ # Open temp file and yield to caller
+ f = os.fdopen(fd, mode)
+ yield f
+
+ # Ensure file is closed before rename
+ f.close()
+
+ # Atomic replace
+ await asyncio.get_event_loop().run_in_executor(
+ None, os.replace, tmp_path, filepath
+ )
+
+ except Exception:
+ # Clean up temp file on error
+ try:
+ await asyncio.get_event_loop().run_in_executor(
+ None, os.unlink, tmp_path
+ )
+ except Exception:
+ pass
+ raise
+
+ finally:
+ # Release lock
+ await lock.__aexit__(None, None, None)
+
+
+@asynccontextmanager
+async def locked_read(filepath: str | Path, timeout: float = 5.0):
+ """
+ Async context manager for locked file reading.
+
+ Acquires shared lock for reading, allowing multiple concurrent readers
+ but blocking writers.
+
+ Args:
+ filepath: File path to read
+ timeout: Lock timeout in seconds (default: 5.0)
+
+ Example:
+ async with locked_read("/path/to/file.json", timeout=5.0) as f:
+ data = json.load(f)
+
+ Raises:
+ FileLockTimeout: If lock cannot be acquired within timeout
+ FileNotFoundError: If file doesn't exist
+ """
+ filepath = Path(filepath)
+
+ if not filepath.exists():
+ raise FileNotFoundError(f"File not found: {filepath}")
+
+ # Acquire shared lock (allows multiple readers)
+ lock = FileLock(filepath, timeout=timeout, exclusive=False)
+ await lock.__aenter__()
+
+ try:
+ # Open file for reading
+ with open(filepath) as f:
+ yield f
+ finally:
+ # Release lock
+ await lock.__aexit__(None, None, None)
+
+
+async def locked_json_write(
+ filepath: str | Path, data: Any, timeout: float = 5.0, indent: int = 2
+) -> None:
+ """
+ Helper function for writing JSON with locking and atomicity.
+
+ Args:
+ filepath: Target file path
+ data: Data to serialize as JSON
+ timeout: Lock timeout in seconds (default: 5.0)
+ indent: JSON indentation (default: 2)
+
+ Example:
+ await locked_json_write("/path/to/file.json", {"key": "value"})
+
+ Raises:
+ FileLockTimeout: If lock cannot be acquired within timeout
+ """
+ async with locked_write(filepath, timeout=timeout) as f:
+ json.dump(data, f, indent=indent)
+
+
+async def locked_json_read(filepath: str | Path, timeout: float = 5.0) -> Any:
+ """
+ Helper function for reading JSON with locking.
+
+ Args:
+ filepath: File path to read
+ timeout: Lock timeout in seconds (default: 5.0)
+
+ Returns:
+ Parsed JSON data
+
+ Example:
+ data = await locked_json_read("/path/to/file.json")
+
+ Raises:
+ FileLockTimeout: If lock cannot be acquired within timeout
+ FileNotFoundError: If file doesn't exist
+ json.JSONDecodeError: If file contains invalid JSON
+ """
+ async with locked_read(filepath, timeout=timeout) as f:
+ return json.load(f)
+
+
+async def locked_json_update(
+ filepath: str | Path, updater: callable, timeout: float = 5.0, indent: int = 2
+) -> Any:
+ """
+ Helper for atomic read-modify-write of JSON files.
+
+ Acquires exclusive lock, reads current data, applies updater function,
+ writes updated data atomically.
+
+ Args:
+ filepath: File path to update
+ updater: Function that takes current data and returns updated data
+ timeout: Lock timeout in seconds (default: 5.0)
+ indent: JSON indentation (default: 2)
+
+ Returns:
+ Updated data
+
+ Example:
+ def add_item(data):
+ data["items"].append({"new": "item"})
+ return data
+
+ updated = await locked_json_update("/path/to/file.json", add_item)
+
+ Raises:
+ FileLockTimeout: If lock cannot be acquired within timeout
+ """
+ filepath = Path(filepath)
+
+ # Acquire exclusive lock
+ lock = FileLock(filepath, timeout=timeout, exclusive=True)
+ await lock.__aenter__()
+
+ try:
+ # Read current data
+ if filepath.exists():
+ with open(filepath) as f:
+ data = json.load(f)
+ else:
+ data = None
+
+ # Apply update function
+ updated_data = updater(data)
+
+ # Write atomically
+ fd, tmp_path = await asyncio.get_event_loop().run_in_executor(
+ None,
+ lambda: tempfile.mkstemp(
+ dir=filepath.parent, prefix=f".{filepath.name}.tmp.", suffix=""
+ ),
+ )
+
+ try:
+ with os.fdopen(fd, "w") as f:
+ json.dump(updated_data, f, indent=indent)
+
+ await asyncio.get_event_loop().run_in_executor(
+ None, os.replace, tmp_path, filepath
+ )
+
+ except Exception:
+ try:
+ await asyncio.get_event_loop().run_in_executor(
+ None, os.unlink, tmp_path
+ )
+ except Exception:
+ pass
+ raise
+
+ return updated_data
+
+ finally:
+ await lock.__aexit__(None, None, None)
diff --git a/apps/backend/runners/github/gh_client.py b/apps/backend/runners/github/gh_client.py
new file mode 100644
index 00000000..84fa7b2b
--- /dev/null
+++ b/apps/backend/runners/github/gh_client.py
@@ -0,0 +1,711 @@
+"""
+GitHub CLI Client with Timeout and Retry Logic
+==============================================
+
+Wrapper for gh CLI commands that prevents hung processes through:
+- Configurable timeouts (default 30s)
+- Exponential backoff retry (3 attempts: 1s, 2s, 4s)
+- Structured logging for monitoring
+- Async subprocess execution for non-blocking operations
+
+This eliminates the risk of indefinite hangs in GitHub automation workflows.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any
+
+try:
+ from .rate_limiter import RateLimiter, RateLimitExceeded
+except (ImportError, ValueError, SystemError):
+ from rate_limiter import RateLimiter, RateLimitExceeded
+
+# Configure logger
+logger = logging.getLogger(__name__)
+
+
+class GHTimeoutError(Exception):
+ """Raised when gh CLI command times out after all retry attempts."""
+
+ pass
+
+
+class GHCommandError(Exception):
+ """Raised when gh CLI command fails with non-zero exit code."""
+
+ pass
+
+
+class PRTooLargeError(Exception):
+ """Raised when PR diff exceeds GitHub's 20,000 line limit."""
+
+ pass
+
+
+@dataclass
+class GHCommandResult:
+ """Result of a gh CLI command execution."""
+
+ stdout: str
+ stderr: str
+ returncode: int
+ command: list[str]
+ attempts: int
+ total_time: float
+
+
+class GHClient:
+ """
+ Async client for GitHub CLI with timeout and retry protection.
+
+ Usage:
+ client = GHClient(project_dir=Path("/path/to/project"))
+
+ # Simple command
+ result = await client.run(["pr", "list"])
+
+ # With custom timeout
+ result = await client.run(["pr", "diff", "123"], timeout=60.0)
+
+ # Convenience methods
+ pr_data = await client.pr_get(123)
+ diff = await client.pr_diff(123)
+ await client.pr_review(123, body="LGTM", event="approve")
+ """
+
+ def __init__(
+ self,
+ project_dir: Path,
+ default_timeout: float = 30.0,
+ max_retries: int = 3,
+ enable_rate_limiting: bool = True,
+ ):
+ """
+ Initialize GitHub CLI client.
+
+ Args:
+ project_dir: Project directory for gh commands
+ default_timeout: Default timeout in seconds for commands
+ max_retries: Maximum number of retry attempts
+ enable_rate_limiting: Whether to enforce rate limiting (default: True)
+ """
+ self.project_dir = Path(project_dir)
+ self.default_timeout = default_timeout
+ self.max_retries = max_retries
+ self.enable_rate_limiting = enable_rate_limiting
+
+ # Initialize rate limiter singleton
+ if enable_rate_limiting:
+ self._rate_limiter = RateLimiter.get_instance()
+
+ async def run(
+ self,
+ args: list[str],
+ timeout: float | None = None,
+ raise_on_error: bool = True,
+ ) -> GHCommandResult:
+ """
+ Execute a gh CLI command with timeout and retry logic.
+
+ Args:
+ args: Command arguments (e.g., ["pr", "list"])
+ timeout: Timeout in seconds (uses default if None)
+ raise_on_error: Raise GHCommandError on non-zero exit
+
+ Returns:
+ GHCommandResult with command output and metadata
+
+ Raises:
+ GHTimeoutError: If command times out after all retries
+ GHCommandError: If command fails and raise_on_error is True
+ """
+ timeout = timeout or self.default_timeout
+ cmd = ["gh"] + args
+ start_time = asyncio.get_event_loop().time()
+
+ # Pre-flight rate limit check
+ if self.enable_rate_limiting:
+ available, msg = self._rate_limiter.check_github_available()
+ if not available:
+ # Try to acquire (will wait if needed)
+ logger.info(f"Rate limited, waiting for token: {msg}")
+ if not await self._rate_limiter.acquire_github(timeout=30.0):
+ raise RateLimitExceeded(f"GitHub API rate limit exceeded: {msg}")
+ else:
+ # Consume a token for this request
+ await self._rate_limiter.acquire_github(timeout=1.0)
+
+ for attempt in range(1, self.max_retries + 1):
+ try:
+ logger.debug(
+ f"Executing gh command (attempt {attempt}/{self.max_retries}): {' '.join(cmd)}"
+ )
+
+ # Create subprocess
+ proc = await asyncio.create_subprocess_exec(
+ *cmd,
+ cwd=self.project_dir,
+ stdout=asyncio.subprocess.PIPE,
+ stderr=asyncio.subprocess.PIPE,
+ )
+
+ # Wait for completion with timeout
+ try:
+ stdout, stderr = await asyncio.wait_for(
+ proc.communicate(), timeout=timeout
+ )
+ except asyncio.TimeoutError:
+ # Kill the hung process
+ try:
+ proc.kill()
+ await proc.wait()
+ except Exception as e:
+ logger.warning(f"Failed to kill hung process: {e}")
+
+ # Calculate backoff delay
+ backoff_delay = 2 ** (attempt - 1)
+
+ logger.warning(
+ f"gh {args[0]} timed out after {timeout}s "
+ f"(attempt {attempt}/{self.max_retries})"
+ )
+
+ # Retry if attempts remain
+ if attempt < self.max_retries:
+ logger.info(f"Retrying in {backoff_delay}s...")
+ await asyncio.sleep(backoff_delay)
+ continue
+ else:
+ # All retries exhausted
+ total_time = asyncio.get_event_loop().time() - start_time
+ logger.error(
+ f"gh {args[0]} timed out after {self.max_retries} attempts "
+ f"({total_time:.1f}s total)"
+ )
+ raise GHTimeoutError(
+ f"gh {args[0]} timed out after {self.max_retries} attempts "
+ f"({timeout}s each, {total_time:.1f}s total)"
+ )
+
+ # Successful execution (no timeout)
+ total_time = asyncio.get_event_loop().time() - start_time
+ stdout_str = stdout.decode("utf-8")
+ stderr_str = stderr.decode("utf-8")
+
+ result = GHCommandResult(
+ stdout=stdout_str,
+ stderr=stderr_str,
+ returncode=proc.returncode or 0,
+ command=cmd,
+ attempts=attempt,
+ total_time=total_time,
+ )
+
+ if result.returncode != 0:
+ logger.warning(
+ f"gh {args[0]} failed with exit code {result.returncode}: {stderr_str}"
+ )
+
+ # Check for rate limit errors (403/429)
+ error_lower = stderr_str.lower()
+ if (
+ "403" in stderr_str
+ or "429" in stderr_str
+ or "rate limit" in error_lower
+ ):
+ if self.enable_rate_limiting:
+ self._rate_limiter.record_github_error()
+ raise RateLimitExceeded(
+ f"GitHub API rate limit (HTTP 403/429): {stderr_str}"
+ )
+
+ if raise_on_error:
+ raise GHCommandError(
+ f"gh {args[0]} failed: {stderr_str or 'Unknown error'}"
+ )
+ else:
+ logger.debug(
+ f"gh {args[0]} completed successfully "
+ f"(attempt {attempt}, {total_time:.2f}s)"
+ )
+
+ return result
+
+ except (GHTimeoutError, GHCommandError, RateLimitExceeded):
+ # Re-raise our custom exceptions
+ raise
+ except Exception as e:
+ # Unexpected error
+ logger.error(f"Unexpected error in gh command: {e}")
+ if attempt == self.max_retries:
+ raise GHCommandError(f"gh {args[0]} failed: {str(e)}")
+ else:
+ # Retry on unexpected errors too
+ backoff_delay = 2 ** (attempt - 1)
+ logger.info(f"Retrying in {backoff_delay}s after error...")
+ await asyncio.sleep(backoff_delay)
+ continue
+
+ # Should never reach here, but for type safety
+ raise GHCommandError(f"gh {args[0]} failed after {self.max_retries} attempts")
+
+ # =========================================================================
+ # Convenience methods for common gh commands
+ # =========================================================================
+
+ async def pr_list(
+ self,
+ state: str = "open",
+ limit: int = 100,
+ json_fields: list[str] | None = None,
+ ) -> list[dict[str, Any]]:
+ """
+ List pull requests.
+
+ Args:
+ state: PR state (open, closed, merged, all)
+ limit: Maximum number of PRs to return
+ json_fields: Fields to include in JSON output
+
+ Returns:
+ List of PR data dictionaries
+ """
+ if json_fields is None:
+ json_fields = [
+ "number",
+ "title",
+ "state",
+ "author",
+ "headRefName",
+ "baseRefName",
+ ]
+
+ args = [
+ "pr",
+ "list",
+ "--state",
+ state,
+ "--limit",
+ str(limit),
+ "--json",
+ ",".join(json_fields),
+ ]
+
+ result = await self.run(args)
+ return json.loads(result.stdout)
+
+ async def pr_get(
+ self, pr_number: int, json_fields: list[str] | None = None
+ ) -> dict[str, Any]:
+ """
+ Get PR data by number.
+
+ Args:
+ pr_number: PR number
+ json_fields: Fields to include in JSON output
+
+ Returns:
+ PR data dictionary
+ """
+ if json_fields is None:
+ json_fields = [
+ "number",
+ "title",
+ "body",
+ "state",
+ "headRefName",
+ "baseRefName",
+ "author",
+ "files",
+ "additions",
+ "deletions",
+ "changedFiles",
+ ]
+
+ args = [
+ "pr",
+ "view",
+ str(pr_number),
+ "--json",
+ ",".join(json_fields),
+ ]
+
+ result = await self.run(args)
+ return json.loads(result.stdout)
+
+ async def pr_diff(self, pr_number: int) -> str:
+ """
+ Get PR diff.
+
+ Args:
+ pr_number: PR number
+
+ Returns:
+ Unified diff string
+
+ Raises:
+ PRTooLargeError: If PR exceeds GitHub's 20,000 line diff limit
+ """
+ args = ["pr", "diff", str(pr_number)]
+ try:
+ result = await self.run(args)
+ return result.stdout
+ except GHCommandError as e:
+ # Check if error is due to PR being too large
+ error_msg = str(e)
+ if (
+ "diff exceeded the maximum number of lines" in error_msg
+ or "HTTP 406" in error_msg
+ ):
+ raise PRTooLargeError(
+ f"PR #{pr_number} exceeds GitHub's 20,000 line diff limit. "
+ "Consider splitting into smaller PRs or review files individually."
+ ) from e
+ # Re-raise other command errors
+ raise
+
+ async def pr_review(
+ self,
+ pr_number: int,
+ body: str,
+ event: str = "comment",
+ ) -> int:
+ """
+ Post a review to a PR.
+
+ Args:
+ pr_number: PR number
+ body: Review comment body
+ event: Review event (approve, request-changes, comment)
+
+ Returns:
+ Review ID (currently 0, as gh CLI doesn't return ID)
+ """
+ args = ["pr", "review", str(pr_number)]
+
+ if event.lower() == "approve":
+ args.append("--approve")
+ elif event.lower() in ["request-changes", "request_changes"]:
+ args.append("--request-changes")
+ else:
+ args.append("--comment")
+
+ args.extend(["--body", body])
+
+ await self.run(args)
+ return 0 # gh CLI doesn't return review ID
+
+ async def issue_list(
+ self,
+ state: str = "open",
+ limit: int = 100,
+ json_fields: list[str] | None = None,
+ ) -> list[dict[str, Any]]:
+ """
+ List issues.
+
+ Args:
+ state: Issue state (open, closed, all)
+ limit: Maximum number of issues to return
+ json_fields: Fields to include in JSON output
+
+ Returns:
+ List of issue data dictionaries
+ """
+ if json_fields is None:
+ json_fields = [
+ "number",
+ "title",
+ "body",
+ "labels",
+ "author",
+ "createdAt",
+ "updatedAt",
+ "comments",
+ ]
+
+ args = [
+ "issue",
+ "list",
+ "--state",
+ state,
+ "--limit",
+ str(limit),
+ "--json",
+ ",".join(json_fields),
+ ]
+
+ result = await self.run(args)
+ return json.loads(result.stdout)
+
+ async def issue_get(
+ self, issue_number: int, json_fields: list[str] | None = None
+ ) -> dict[str, Any]:
+ """
+ Get issue data by number.
+
+ Args:
+ issue_number: Issue number
+ json_fields: Fields to include in JSON output
+
+ Returns:
+ Issue data dictionary
+ """
+ if json_fields is None:
+ json_fields = [
+ "number",
+ "title",
+ "body",
+ "state",
+ "labels",
+ "author",
+ "comments",
+ "createdAt",
+ "updatedAt",
+ ]
+
+ args = [
+ "issue",
+ "view",
+ str(issue_number),
+ "--json",
+ ",".join(json_fields),
+ ]
+
+ result = await self.run(args)
+ return json.loads(result.stdout)
+
+ async def issue_comment(self, issue_number: int, body: str) -> None:
+ """
+ Post a comment to an issue.
+
+ Args:
+ issue_number: Issue number
+ body: Comment body
+ """
+ args = ["issue", "comment", str(issue_number), "--body", body]
+ await self.run(args)
+
+ async def issue_add_labels(self, issue_number: int, labels: list[str]) -> None:
+ """
+ Add labels to an issue.
+
+ Args:
+ issue_number: Issue number
+ labels: List of label names to add
+ """
+ if not labels:
+ return
+
+ args = [
+ "issue",
+ "edit",
+ str(issue_number),
+ "--add-label",
+ ",".join(labels),
+ ]
+ await self.run(args)
+
+ async def issue_remove_labels(self, issue_number: int, labels: list[str]) -> None:
+ """
+ Remove labels from an issue.
+
+ Args:
+ issue_number: Issue number
+ labels: List of label names to remove
+ """
+ if not labels:
+ return
+
+ args = [
+ "issue",
+ "edit",
+ str(issue_number),
+ "--remove-label",
+ ",".join(labels),
+ ]
+ # Don't raise on error - labels might not exist
+ await self.run(args, raise_on_error=False)
+
+ async def api_get(self, endpoint: str, params: dict[str, str] | None = None) -> Any:
+ """
+ Make a GET request to GitHub API.
+
+ Args:
+ endpoint: API endpoint (e.g., "/repos/owner/repo/contents/path")
+ params: Query parameters
+
+ Returns:
+ JSON response
+ """
+ args = ["api", endpoint]
+
+ if params:
+ for key, value in params.items():
+ args.extend(["-f", f"{key}={value}"])
+
+ result = await self.run(args)
+ return json.loads(result.stdout)
+
+ async def pr_merge(
+ self,
+ pr_number: int,
+ merge_method: str = "squash",
+ commit_title: str | None = None,
+ commit_message: str | None = None,
+ ) -> None:
+ """
+ Merge a pull request.
+
+ Args:
+ pr_number: PR number to merge
+ merge_method: Merge method - "merge", "squash", or "rebase" (default: "squash")
+ commit_title: Custom commit title (optional)
+ commit_message: Custom commit message (optional)
+ """
+ args = ["pr", "merge", str(pr_number), f"--{merge_method}"]
+
+ if commit_title:
+ args.extend(["--subject", commit_title])
+ if commit_message:
+ args.extend(["--body", commit_message])
+
+ await self.run(args)
+
+ async def pr_comment(self, pr_number: int, body: str) -> None:
+ """
+ Post a comment on a pull request.
+
+ Args:
+ pr_number: PR number
+ body: Comment body
+ """
+ args = ["pr", "comment", str(pr_number), "--body", body]
+ await self.run(args)
+
+ async def pr_get_assignees(self, pr_number: int) -> list[str]:
+ """
+ Get assignees for a pull request.
+
+ Args:
+ pr_number: PR number
+
+ Returns:
+ List of assignee logins
+ """
+ data = await self.pr_get(pr_number, json_fields=["assignees"])
+ assignees = data.get("assignees", [])
+ return [a["login"] for a in assignees]
+
+ async def pr_assign(self, pr_number: int, assignees: list[str]) -> None:
+ """
+ Assign users to a pull request.
+
+ Args:
+ pr_number: PR number
+ assignees: List of GitHub usernames to assign
+ """
+ if not assignees:
+ return
+
+ # Use gh api to add assignees
+ endpoint = f"/repos/{{owner}}/{{repo}}/issues/{pr_number}/assignees"
+ args = [
+ "api",
+ endpoint,
+ "-X",
+ "POST",
+ "-f",
+ f"assignees={','.join(assignees)}",
+ ]
+ await self.run(args)
+
+ async def compare_commits(self, base_sha: str, head_sha: str) -> dict[str, Any]:
+ """
+ Compare two commits to get changes between them.
+
+ Uses: GET /repos/{owner}/{repo}/compare/{base}...{head}
+
+ Args:
+ base_sha: Base commit SHA (e.g., last reviewed commit)
+ head_sha: Head commit SHA (e.g., current PR HEAD)
+
+ Returns:
+ Dict with:
+ - commits: List of commits between base and head
+ - files: List of changed files with patches
+ - ahead_by: Number of commits head is ahead of base
+ - behind_by: Number of commits head is behind base
+ - total_commits: Total number of commits in comparison
+ """
+ endpoint = f"repos/{{owner}}/{{repo}}/compare/{base_sha}...{head_sha}"
+ args = ["api", endpoint]
+
+ result = await self.run(args, timeout=60.0) # Longer timeout for large diffs
+ return json.loads(result.stdout)
+
+ async def get_comments_since(
+ self, pr_number: int, since_timestamp: str
+ ) -> dict[str, list[dict]]:
+ """
+ Get all comments (review + issue) since a timestamp.
+
+ Args:
+ pr_number: PR number
+ since_timestamp: ISO timestamp to filter from (e.g., "2025-12-25T10:30:00Z")
+
+ Returns:
+ Dict with:
+ - review_comments: Inline review comments on files
+ - issue_comments: General PR discussion comments
+ """
+ # Fetch inline review comments
+ review_endpoint = f"repos/{{owner}}/{{repo}}/pulls/{pr_number}/comments"
+ review_args = ["api", review_endpoint, "-f", f"since={since_timestamp}"]
+ review_result = await self.run(review_args, raise_on_error=False)
+
+ review_comments = []
+ if review_result.returncode == 0:
+ try:
+ review_comments = json.loads(review_result.stdout)
+ except json.JSONDecodeError:
+ logger.warning(f"Failed to parse review comments for PR #{pr_number}")
+
+ # Fetch general issue comments
+ issue_endpoint = f"repos/{{owner}}/{{repo}}/issues/{pr_number}/comments"
+ issue_args = ["api", issue_endpoint, "-f", f"since={since_timestamp}"]
+ issue_result = await self.run(issue_args, raise_on_error=False)
+
+ issue_comments = []
+ if issue_result.returncode == 0:
+ try:
+ issue_comments = json.loads(issue_result.stdout)
+ except json.JSONDecodeError:
+ logger.warning(f"Failed to parse issue comments for PR #{pr_number}")
+
+ return {
+ "review_comments": review_comments,
+ "issue_comments": issue_comments,
+ }
+
+ async def get_pr_head_sha(self, pr_number: int) -> str | None:
+ """
+ Get the current HEAD SHA of a PR.
+
+ Args:
+ pr_number: PR number
+
+ Returns:
+ HEAD commit SHA or None if not found
+ """
+ data = await self.pr_get(pr_number, json_fields=["commits"])
+ commits = data.get("commits", [])
+ if commits:
+ # Last commit is the HEAD
+ return commits[-1].get("oid")
+ return None
diff --git a/apps/backend/runners/github/learning.py b/apps/backend/runners/github/learning.py
new file mode 100644
index 00000000..f2389a97
--- /dev/null
+++ b/apps/backend/runners/github/learning.py
@@ -0,0 +1,644 @@
+"""
+Learning Loop & Outcome Tracking
+================================
+
+Tracks review outcomes, predictions, and accuracy to enable system improvement.
+
+Features:
+- ReviewOutcome model for tracking predictions vs actual results
+- Accuracy metrics per-repo and aggregate
+- Pattern detection for cross-project learning
+- Feedback loop for prompt optimization
+
+Usage:
+ tracker = LearningTracker(state_dir=Path(".auto-claude/github"))
+
+ # Record a prediction
+ tracker.record_prediction("repo", review_id, "request_changes", findings)
+
+ # Later, record the outcome
+ tracker.record_outcome("repo", review_id, "merged", time_to_merge=timedelta(hours=2))
+
+ # Get accuracy metrics
+ metrics = tracker.get_accuracy("repo")
+"""
+
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass, field
+from datetime import datetime, timedelta, timezone
+from enum import Enum
+from pathlib import Path
+from typing import Any
+
+
+class PredictionType(str, Enum):
+ """Types of predictions the system makes."""
+
+ REVIEW_APPROVE = "review_approve"
+ REVIEW_REQUEST_CHANGES = "review_request_changes"
+ TRIAGE_BUG = "triage_bug"
+ TRIAGE_FEATURE = "triage_feature"
+ TRIAGE_SPAM = "triage_spam"
+ TRIAGE_DUPLICATE = "triage_duplicate"
+ AUTOFIX_WILL_WORK = "autofix_will_work"
+ LABEL_APPLIED = "label_applied"
+
+
+class OutcomeType(str, Enum):
+ """Actual outcomes that occurred."""
+
+ MERGED = "merged"
+ CLOSED = "closed"
+ MODIFIED = "modified" # Changes requested, author modified
+ REJECTED = "rejected" # Override or reversal
+ OVERRIDDEN = "overridden" # User overrode the action
+ IGNORED = "ignored" # No action taken by user
+ CONFIRMED = "confirmed" # User confirmed correct
+ STALE = "stale" # Too old to determine
+
+
+class AuthorResponse(str, Enum):
+ """How the PR/issue author responded to the action."""
+
+ ACCEPTED = "accepted" # Made requested changes
+ DISPUTED = "disputed" # Pushed back on feedback
+ IGNORED = "ignored" # No response
+ THANKED = "thanked" # Positive acknowledgment
+ UNKNOWN = "unknown" # Can't determine
+
+
+@dataclass
+class ReviewOutcome:
+ """
+ Tracks prediction vs actual outcome for a review.
+
+ Used to calculate accuracy and identify patterns.
+ """
+
+ review_id: str
+ repo: str
+ pr_number: int
+ prediction: PredictionType
+ findings_count: int
+ high_severity_count: int
+ created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
+
+ # Outcome data (filled in later)
+ actual_outcome: OutcomeType | None = None
+ time_to_outcome: timedelta | None = None
+ author_response: AuthorResponse = AuthorResponse.UNKNOWN
+ outcome_recorded_at: datetime | None = None
+
+ # Context for learning
+ file_types: list[str] = field(default_factory=list)
+ change_size: str = "medium" # small/medium/large based on additions+deletions
+ categories: list[str] = field(default_factory=list) # security, bug, style, etc.
+
+ @property
+ def was_correct(self) -> bool | None:
+ """Determine if the prediction was correct."""
+ if self.actual_outcome is None:
+ return None
+
+ # Review predictions
+ if self.prediction == PredictionType.REVIEW_APPROVE:
+ return self.actual_outcome in {OutcomeType.MERGED, OutcomeType.CONFIRMED}
+ elif self.prediction == PredictionType.REVIEW_REQUEST_CHANGES:
+ return self.actual_outcome in {OutcomeType.MODIFIED, OutcomeType.CONFIRMED}
+
+ # Triage predictions
+ elif self.prediction == PredictionType.TRIAGE_SPAM:
+ return self.actual_outcome in {OutcomeType.CLOSED, OutcomeType.CONFIRMED}
+ elif self.prediction == PredictionType.TRIAGE_DUPLICATE:
+ return self.actual_outcome in {OutcomeType.CLOSED, OutcomeType.CONFIRMED}
+
+ # Override means we were wrong
+ if self.actual_outcome == OutcomeType.OVERRIDDEN:
+ return False
+
+ return None
+
+ @property
+ def is_complete(self) -> bool:
+ """Check if outcome has been recorded."""
+ return self.actual_outcome is not None
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "review_id": self.review_id,
+ "repo": self.repo,
+ "pr_number": self.pr_number,
+ "prediction": self.prediction.value,
+ "findings_count": self.findings_count,
+ "high_severity_count": self.high_severity_count,
+ "created_at": self.created_at.isoformat(),
+ "actual_outcome": self.actual_outcome.value
+ if self.actual_outcome
+ else None,
+ "time_to_outcome": self.time_to_outcome.total_seconds()
+ if self.time_to_outcome
+ else None,
+ "author_response": self.author_response.value,
+ "outcome_recorded_at": self.outcome_recorded_at.isoformat()
+ if self.outcome_recorded_at
+ else None,
+ "file_types": self.file_types,
+ "change_size": self.change_size,
+ "categories": self.categories,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict[str, Any]) -> ReviewOutcome:
+ time_to_outcome = None
+ if data.get("time_to_outcome") is not None:
+ time_to_outcome = timedelta(seconds=data["time_to_outcome"])
+
+ outcome_recorded = None
+ if data.get("outcome_recorded_at"):
+ outcome_recorded = datetime.fromisoformat(data["outcome_recorded_at"])
+
+ return cls(
+ review_id=data["review_id"],
+ repo=data["repo"],
+ pr_number=data["pr_number"],
+ prediction=PredictionType(data["prediction"]),
+ findings_count=data.get("findings_count", 0),
+ high_severity_count=data.get("high_severity_count", 0),
+ created_at=datetime.fromisoformat(data["created_at"]),
+ actual_outcome=OutcomeType(data["actual_outcome"])
+ if data.get("actual_outcome")
+ else None,
+ time_to_outcome=time_to_outcome,
+ author_response=AuthorResponse(data.get("author_response", "unknown")),
+ outcome_recorded_at=outcome_recorded,
+ file_types=data.get("file_types", []),
+ change_size=data.get("change_size", "medium"),
+ categories=data.get("categories", []),
+ )
+
+
+@dataclass
+class AccuracyStats:
+ """Accuracy statistics for a time period or repo."""
+
+ total_predictions: int = 0
+ correct_predictions: int = 0
+ incorrect_predictions: int = 0
+ pending_outcomes: int = 0
+
+ # By prediction type
+ by_type: dict[str, dict[str, int]] = field(default_factory=dict)
+
+ # Time metrics
+ avg_time_to_merge: timedelta | None = None
+ avg_time_to_feedback: timedelta | None = None
+
+ @property
+ def accuracy(self) -> float:
+ """Overall accuracy rate."""
+ resolved = self.correct_predictions + self.incorrect_predictions
+ if resolved == 0:
+ return 0.0
+ return self.correct_predictions / resolved
+
+ @property
+ def completion_rate(self) -> float:
+ """Rate of outcomes tracked."""
+ if self.total_predictions == 0:
+ return 0.0
+ return (self.total_predictions - self.pending_outcomes) / self.total_predictions
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "total_predictions": self.total_predictions,
+ "correct_predictions": self.correct_predictions,
+ "incorrect_predictions": self.incorrect_predictions,
+ "pending_outcomes": self.pending_outcomes,
+ "accuracy": self.accuracy,
+ "completion_rate": self.completion_rate,
+ "by_type": self.by_type,
+ "avg_time_to_merge": self.avg_time_to_merge.total_seconds()
+ if self.avg_time_to_merge
+ else None,
+ }
+
+
+@dataclass
+class LearningPattern:
+ """
+ Detected pattern for cross-project learning.
+
+ Anonymized and aggregated for privacy.
+ """
+
+ pattern_id: str
+ pattern_type: str # e.g., "file_type_accuracy", "category_accuracy"
+ context: dict[str, Any] # e.g., {"file_type": "py", "category": "security"}
+ sample_size: int
+ accuracy: float
+ confidence: float # Based on sample size
+ created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
+ updated_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "pattern_id": self.pattern_id,
+ "pattern_type": self.pattern_type,
+ "context": self.context,
+ "sample_size": self.sample_size,
+ "accuracy": self.accuracy,
+ "confidence": self.confidence,
+ "created_at": self.created_at.isoformat(),
+ "updated_at": self.updated_at.isoformat(),
+ }
+
+
+class LearningTracker:
+ """
+ Tracks predictions and outcomes to enable learning.
+
+ Usage:
+ tracker = LearningTracker(state_dir=Path(".auto-claude/github"))
+
+ # Record prediction when making a review
+ tracker.record_prediction(
+ repo="owner/repo",
+ review_id="review-123",
+ prediction=PredictionType.REVIEW_REQUEST_CHANGES,
+ findings_count=5,
+ high_severity_count=2,
+ file_types=["py", "ts"],
+ categories=["security", "bug"],
+ )
+
+ # Later, record outcome
+ tracker.record_outcome(
+ repo="owner/repo",
+ review_id="review-123",
+ outcome=OutcomeType.MODIFIED,
+ time_to_outcome=timedelta(hours=2),
+ author_response=AuthorResponse.ACCEPTED,
+ )
+ """
+
+ def __init__(self, state_dir: Path):
+ self.state_dir = state_dir
+ self.learning_dir = state_dir / "learning"
+ self.learning_dir.mkdir(parents=True, exist_ok=True)
+
+ self._outcomes: dict[str, ReviewOutcome] = {}
+ self._load_outcomes()
+
+ def _get_outcomes_file(self, repo: str) -> Path:
+ safe_name = repo.replace("/", "_")
+ return self.learning_dir / f"{safe_name}_outcomes.json"
+
+ def _load_outcomes(self) -> None:
+ """Load all outcomes from disk."""
+ for file in self.learning_dir.glob("*_outcomes.json"):
+ try:
+ with open(file) as f:
+ data = json.load(f)
+ for item in data.get("outcomes", []):
+ outcome = ReviewOutcome.from_dict(item)
+ self._outcomes[outcome.review_id] = outcome
+ except (json.JSONDecodeError, KeyError):
+ continue
+
+ def _save_outcomes(self, repo: str) -> None:
+ """Save outcomes for a repo to disk with file locking for concurrency safety."""
+ from .file_lock import FileLock, atomic_write
+
+ file = self._get_outcomes_file(repo)
+ repo_outcomes = [o for o in self._outcomes.values() if o.repo == repo]
+
+ data = {
+ "repo": repo,
+ "updated_at": datetime.now(timezone.utc).isoformat(),
+ "outcomes": [o.to_dict() for o in repo_outcomes],
+ }
+
+ # Use file locking and atomic write for safe concurrent access
+ with FileLock(file, timeout=5.0):
+ with atomic_write(file) as f:
+ json.dump(data, f, indent=2)
+
+ def record_prediction(
+ self,
+ repo: str,
+ review_id: str,
+ prediction: PredictionType,
+ pr_number: int = 0,
+ findings_count: int = 0,
+ high_severity_count: int = 0,
+ file_types: list[str] | None = None,
+ change_size: str = "medium",
+ categories: list[str] | None = None,
+ ) -> ReviewOutcome:
+ """
+ Record a prediction made by the system.
+
+ Args:
+ repo: Repository
+ review_id: Unique identifier for this review
+ prediction: The prediction type
+ pr_number: PR number (if applicable)
+ findings_count: Number of findings
+ high_severity_count: High severity findings
+ file_types: File types involved
+ change_size: Size category (small/medium/large)
+ categories: Finding categories
+
+ Returns:
+ The created ReviewOutcome
+ """
+ outcome = ReviewOutcome(
+ review_id=review_id,
+ repo=repo,
+ pr_number=pr_number,
+ prediction=prediction,
+ findings_count=findings_count,
+ high_severity_count=high_severity_count,
+ file_types=file_types or [],
+ change_size=change_size,
+ categories=categories or [],
+ )
+
+ self._outcomes[review_id] = outcome
+ self._save_outcomes(repo)
+
+ return outcome
+
+ def record_outcome(
+ self,
+ repo: str,
+ review_id: str,
+ outcome: OutcomeType,
+ time_to_outcome: timedelta | None = None,
+ author_response: AuthorResponse = AuthorResponse.UNKNOWN,
+ ) -> ReviewOutcome | None:
+ """
+ Record the actual outcome for a prediction.
+
+ Args:
+ repo: Repository
+ review_id: The review ID to update
+ outcome: What actually happened
+ time_to_outcome: Time from prediction to outcome
+ author_response: How the author responded
+
+ Returns:
+ Updated ReviewOutcome or None if not found
+ """
+ if review_id not in self._outcomes:
+ return None
+
+ review_outcome = self._outcomes[review_id]
+ review_outcome.actual_outcome = outcome
+ review_outcome.time_to_outcome = time_to_outcome
+ review_outcome.author_response = author_response
+ review_outcome.outcome_recorded_at = datetime.now(timezone.utc)
+
+ self._save_outcomes(repo)
+
+ return review_outcome
+
+ def get_pending_outcomes(self, repo: str | None = None) -> list[ReviewOutcome]:
+ """Get predictions that don't have outcomes yet."""
+ pending = []
+ for outcome in self._outcomes.values():
+ if not outcome.is_complete:
+ if repo is None or outcome.repo == repo:
+ pending.append(outcome)
+ return pending
+
+ def get_accuracy(
+ self,
+ repo: str | None = None,
+ since: datetime | None = None,
+ prediction_type: PredictionType | None = None,
+ ) -> AccuracyStats:
+ """
+ Get accuracy statistics.
+
+ Args:
+ repo: Filter by repo (None for all)
+ since: Only include predictions after this time
+ prediction_type: Filter by prediction type
+
+ Returns:
+ AccuracyStats with aggregated metrics
+ """
+ stats = AccuracyStats()
+ merge_times = []
+
+ for outcome in self._outcomes.values():
+ # Apply filters
+ if repo and outcome.repo != repo:
+ continue
+ if since and outcome.created_at < since:
+ continue
+ if prediction_type and outcome.prediction != prediction_type:
+ continue
+
+ stats.total_predictions += 1
+
+ # Track by type
+ type_key = outcome.prediction.value
+ if type_key not in stats.by_type:
+ stats.by_type[type_key] = {"total": 0, "correct": 0, "incorrect": 0}
+ stats.by_type[type_key]["total"] += 1
+
+ if outcome.is_complete:
+ was_correct = outcome.was_correct
+ if was_correct is True:
+ stats.correct_predictions += 1
+ stats.by_type[type_key]["correct"] += 1
+ elif was_correct is False:
+ stats.incorrect_predictions += 1
+ stats.by_type[type_key]["incorrect"] += 1
+
+ # Track merge times
+ if (
+ outcome.actual_outcome == OutcomeType.MERGED
+ and outcome.time_to_outcome
+ ):
+ merge_times.append(outcome.time_to_outcome)
+ else:
+ stats.pending_outcomes += 1
+
+ # Calculate average merge time
+ if merge_times:
+ avg_seconds = sum(t.total_seconds() for t in merge_times) / len(merge_times)
+ stats.avg_time_to_merge = timedelta(seconds=avg_seconds)
+
+ return stats
+
+ def get_recent_outcomes(
+ self,
+ repo: str | None = None,
+ limit: int = 50,
+ ) -> list[ReviewOutcome]:
+ """Get recent outcomes, most recent first."""
+ outcomes = list(self._outcomes.values())
+
+ if repo:
+ outcomes = [o for o in outcomes if o.repo == repo]
+
+ outcomes.sort(key=lambda o: o.created_at, reverse=True)
+ return outcomes[:limit]
+
+ def detect_patterns(self, min_sample_size: int = 20) -> list[LearningPattern]:
+ """
+ Detect learning patterns from outcomes.
+
+ Aggregates data to identify where the system performs well or poorly.
+
+ Args:
+ min_sample_size: Minimum samples to create a pattern
+
+ Returns:
+ List of detected patterns
+ """
+ patterns = []
+
+ # Pattern: Accuracy by file type
+ by_file_type: dict[str, dict[str, int]] = {}
+ for outcome in self._outcomes.values():
+ if not outcome.is_complete or outcome.was_correct is None:
+ continue
+
+ for file_type in outcome.file_types:
+ if file_type not in by_file_type:
+ by_file_type[file_type] = {"correct": 0, "incorrect": 0}
+
+ if outcome.was_correct:
+ by_file_type[file_type]["correct"] += 1
+ else:
+ by_file_type[file_type]["incorrect"] += 1
+
+ for file_type, counts in by_file_type.items():
+ total = counts["correct"] + counts["incorrect"]
+ if total >= min_sample_size:
+ accuracy = counts["correct"] / total
+ confidence = min(1.0, total / 100) # More samples = higher confidence
+
+ patterns.append(
+ LearningPattern(
+ pattern_id=f"file_type_{file_type}",
+ pattern_type="file_type_accuracy",
+ context={"file_type": file_type},
+ sample_size=total,
+ accuracy=accuracy,
+ confidence=confidence,
+ )
+ )
+
+ # Pattern: Accuracy by category
+ by_category: dict[str, dict[str, int]] = {}
+ for outcome in self._outcomes.values():
+ if not outcome.is_complete or outcome.was_correct is None:
+ continue
+
+ for category in outcome.categories:
+ if category not in by_category:
+ by_category[category] = {"correct": 0, "incorrect": 0}
+
+ if outcome.was_correct:
+ by_category[category]["correct"] += 1
+ else:
+ by_category[category]["incorrect"] += 1
+
+ for category, counts in by_category.items():
+ total = counts["correct"] + counts["incorrect"]
+ if total >= min_sample_size:
+ accuracy = counts["correct"] / total
+ confidence = min(1.0, total / 100)
+
+ patterns.append(
+ LearningPattern(
+ pattern_id=f"category_{category}",
+ pattern_type="category_accuracy",
+ context={"category": category},
+ sample_size=total,
+ accuracy=accuracy,
+ confidence=confidence,
+ )
+ )
+
+ # Pattern: Accuracy by change size
+ by_size: dict[str, dict[str, int]] = {}
+ for outcome in self._outcomes.values():
+ if not outcome.is_complete or outcome.was_correct is None:
+ continue
+
+ size = outcome.change_size
+ if size not in by_size:
+ by_size[size] = {"correct": 0, "incorrect": 0}
+
+ if outcome.was_correct:
+ by_size[size]["correct"] += 1
+ else:
+ by_size[size]["incorrect"] += 1
+
+ for size, counts in by_size.items():
+ total = counts["correct"] + counts["incorrect"]
+ if total >= min_sample_size:
+ accuracy = counts["correct"] / total
+ confidence = min(1.0, total / 100)
+
+ patterns.append(
+ LearningPattern(
+ pattern_id=f"change_size_{size}",
+ pattern_type="change_size_accuracy",
+ context={"change_size": size},
+ sample_size=total,
+ accuracy=accuracy,
+ confidence=confidence,
+ )
+ )
+
+ return patterns
+
+ def get_dashboard_data(self, repo: str | None = None) -> dict[str, Any]:
+ """
+ Get data for an accuracy dashboard.
+
+ Returns summary suitable for UI display.
+ """
+ now = datetime.now(timezone.utc)
+ week_ago = now - timedelta(days=7)
+ month_ago = now - timedelta(days=30)
+
+ return {
+ "all_time": self.get_accuracy(repo).to_dict(),
+ "last_week": self.get_accuracy(repo, since=week_ago).to_dict(),
+ "last_month": self.get_accuracy(repo, since=month_ago).to_dict(),
+ "patterns": [p.to_dict() for p in self.detect_patterns()],
+ "recent_outcomes": [
+ o.to_dict() for o in self.get_recent_outcomes(repo, limit=10)
+ ],
+ "pending_count": len(self.get_pending_outcomes(repo)),
+ }
+
+ def check_pr_status(
+ self,
+ repo: str,
+ gh_provider,
+ ) -> int:
+ """
+ Check status of pending outcomes by querying GitHub.
+
+ Args:
+ repo: Repository to check
+ gh_provider: GitHubProvider instance
+
+ Returns:
+ Number of outcomes updated
+ """
+ # This would be called periodically to update pending outcomes
+ # Implementation depends on gh_provider being async
+ # Leaving as stub for now
+ return 0
diff --git a/apps/backend/runners/github/lifecycle.py b/apps/backend/runners/github/lifecycle.py
new file mode 100644
index 00000000..38121fc5
--- /dev/null
+++ b/apps/backend/runners/github/lifecycle.py
@@ -0,0 +1,531 @@
+"""
+Issue Lifecycle & Conflict Resolution
+======================================
+
+Unified state machine for issue lifecycle:
+ new → triaged → approved_for_fix → building → pr_created → reviewed → merged
+
+Prevents conflicting operations:
+- Blocks auto-fix if triage = spam/duplicate
+- Requires triage before auto-fix
+- Auto-generated PRs must pass AI review before human notification
+"""
+
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from enum import Enum
+from pathlib import Path
+from typing import Any
+
+
+class IssueLifecycleState(str, Enum):
+ """Unified issue lifecycle states."""
+
+ # Initial state
+ NEW = "new"
+
+ # Triage states
+ TRIAGING = "triaging"
+ TRIAGED = "triaged"
+ SPAM = "spam"
+ DUPLICATE = "duplicate"
+
+ # Approval states
+ PENDING_APPROVAL = "pending_approval"
+ APPROVED_FOR_FIX = "approved_for_fix"
+ REJECTED = "rejected"
+
+ # Build states
+ SPEC_CREATING = "spec_creating"
+ SPEC_READY = "spec_ready"
+ BUILDING = "building"
+ BUILD_FAILED = "build_failed"
+
+ # PR states
+ PR_CREATING = "pr_creating"
+ PR_CREATED = "pr_created"
+ PR_REVIEWING = "pr_reviewing"
+ PR_CHANGES_REQUESTED = "pr_changes_requested"
+ PR_APPROVED = "pr_approved"
+
+ # Terminal states
+ MERGED = "merged"
+ CLOSED = "closed"
+ WONT_FIX = "wont_fix"
+
+ @classmethod
+ def terminal_states(cls) -> set[IssueLifecycleState]:
+ return {cls.MERGED, cls.CLOSED, cls.WONT_FIX, cls.SPAM, cls.DUPLICATE}
+
+ @classmethod
+ def blocks_auto_fix(cls) -> set[IssueLifecycleState]:
+ """States that block auto-fix."""
+ return {cls.SPAM, cls.DUPLICATE, cls.REJECTED, cls.WONT_FIX}
+
+ @classmethod
+ def requires_triage_first(cls) -> set[IssueLifecycleState]:
+ """States that require triage completion first."""
+ return {cls.NEW, cls.TRIAGING}
+
+
+# Valid state transitions
+VALID_TRANSITIONS: dict[IssueLifecycleState, set[IssueLifecycleState]] = {
+ IssueLifecycleState.NEW: {
+ IssueLifecycleState.TRIAGING,
+ IssueLifecycleState.CLOSED,
+ },
+ IssueLifecycleState.TRIAGING: {
+ IssueLifecycleState.TRIAGED,
+ IssueLifecycleState.SPAM,
+ IssueLifecycleState.DUPLICATE,
+ },
+ IssueLifecycleState.TRIAGED: {
+ IssueLifecycleState.PENDING_APPROVAL,
+ IssueLifecycleState.APPROVED_FOR_FIX,
+ IssueLifecycleState.REJECTED,
+ IssueLifecycleState.CLOSED,
+ },
+ IssueLifecycleState.SPAM: {
+ IssueLifecycleState.TRIAGED, # Override
+ IssueLifecycleState.CLOSED,
+ },
+ IssueLifecycleState.DUPLICATE: {
+ IssueLifecycleState.TRIAGED, # Override
+ IssueLifecycleState.CLOSED,
+ },
+ IssueLifecycleState.PENDING_APPROVAL: {
+ IssueLifecycleState.APPROVED_FOR_FIX,
+ IssueLifecycleState.REJECTED,
+ },
+ IssueLifecycleState.APPROVED_FOR_FIX: {
+ IssueLifecycleState.SPEC_CREATING,
+ IssueLifecycleState.REJECTED,
+ },
+ IssueLifecycleState.REJECTED: {
+ IssueLifecycleState.PENDING_APPROVAL, # Retry
+ IssueLifecycleState.CLOSED,
+ },
+ IssueLifecycleState.SPEC_CREATING: {
+ IssueLifecycleState.SPEC_READY,
+ IssueLifecycleState.BUILD_FAILED,
+ },
+ IssueLifecycleState.SPEC_READY: {
+ IssueLifecycleState.BUILDING,
+ IssueLifecycleState.REJECTED,
+ },
+ IssueLifecycleState.BUILDING: {
+ IssueLifecycleState.PR_CREATING,
+ IssueLifecycleState.BUILD_FAILED,
+ },
+ IssueLifecycleState.BUILD_FAILED: {
+ IssueLifecycleState.SPEC_CREATING, # Retry
+ IssueLifecycleState.CLOSED,
+ },
+ IssueLifecycleState.PR_CREATING: {
+ IssueLifecycleState.PR_CREATED,
+ IssueLifecycleState.BUILD_FAILED,
+ },
+ IssueLifecycleState.PR_CREATED: {
+ IssueLifecycleState.PR_REVIEWING,
+ IssueLifecycleState.CLOSED,
+ },
+ IssueLifecycleState.PR_REVIEWING: {
+ IssueLifecycleState.PR_APPROVED,
+ IssueLifecycleState.PR_CHANGES_REQUESTED,
+ },
+ IssueLifecycleState.PR_CHANGES_REQUESTED: {
+ IssueLifecycleState.BUILDING, # Fix loop
+ IssueLifecycleState.CLOSED,
+ },
+ IssueLifecycleState.PR_APPROVED: {
+ IssueLifecycleState.MERGED,
+ IssueLifecycleState.CLOSED,
+ },
+ # Terminal states - no transitions
+ IssueLifecycleState.MERGED: set(),
+ IssueLifecycleState.CLOSED: set(),
+ IssueLifecycleState.WONT_FIX: set(),
+}
+
+
+class ConflictType(str, Enum):
+ """Types of conflicts that can occur."""
+
+ TRIAGE_REQUIRED = "triage_required"
+ BLOCKED_BY_CLASSIFICATION = "blocked_by_classification"
+ INVALID_TRANSITION = "invalid_transition"
+ CONCURRENT_OPERATION = "concurrent_operation"
+ STALE_STATE = "stale_state"
+ REVIEW_REQUIRED = "review_required"
+
+
+@dataclass
+class ConflictResult:
+ """Result of conflict check."""
+
+ has_conflict: bool
+ conflict_type: ConflictType | None = None
+ message: str = ""
+ blocking_state: IssueLifecycleState | None = None
+ resolution_hint: str | None = None
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "has_conflict": self.has_conflict,
+ "conflict_type": self.conflict_type.value if self.conflict_type else None,
+ "message": self.message,
+ "blocking_state": self.blocking_state.value
+ if self.blocking_state
+ else None,
+ "resolution_hint": self.resolution_hint,
+ }
+
+
+@dataclass
+class StateTransition:
+ """Record of a state transition."""
+
+ from_state: IssueLifecycleState
+ to_state: IssueLifecycleState
+ timestamp: str
+ actor: str
+ reason: str | None = None
+ metadata: dict[str, Any] = field(default_factory=dict)
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "from_state": self.from_state.value,
+ "to_state": self.to_state.value,
+ "timestamp": self.timestamp,
+ "actor": self.actor,
+ "reason": self.reason,
+ "metadata": self.metadata,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict[str, Any]) -> StateTransition:
+ return cls(
+ from_state=IssueLifecycleState(data["from_state"]),
+ to_state=IssueLifecycleState(data["to_state"]),
+ timestamp=data["timestamp"],
+ actor=data["actor"],
+ reason=data.get("reason"),
+ metadata=data.get("metadata", {}),
+ )
+
+
+@dataclass
+class IssueLifecycle:
+ """Lifecycle state for a single issue."""
+
+ issue_number: int
+ repo: str
+ current_state: IssueLifecycleState = IssueLifecycleState.NEW
+ triage_result: dict[str, Any] | None = None
+ spec_id: str | None = None
+ pr_number: int | None = None
+ transitions: list[StateTransition] = field(default_factory=list)
+ locked_by: str | None = None # Component holding lock
+ locked_at: str | None = None
+ created_at: str = field(
+ default_factory=lambda: datetime.now(timezone.utc).isoformat()
+ )
+ updated_at: str = field(
+ default_factory=lambda: datetime.now(timezone.utc).isoformat()
+ )
+
+ def can_transition_to(self, new_state: IssueLifecycleState) -> bool:
+ """Check if transition is valid."""
+ valid = VALID_TRANSITIONS.get(self.current_state, set())
+ return new_state in valid
+
+ def transition(
+ self,
+ new_state: IssueLifecycleState,
+ actor: str,
+ reason: str | None = None,
+ metadata: dict[str, Any] | None = None,
+ ) -> ConflictResult:
+ """
+ Attempt to transition to a new state.
+
+ Returns ConflictResult indicating success or conflict.
+ """
+ if not self.can_transition_to(new_state):
+ return ConflictResult(
+ has_conflict=True,
+ conflict_type=ConflictType.INVALID_TRANSITION,
+ message=f"Cannot transition from {self.current_state.value} to {new_state.value}",
+ blocking_state=self.current_state,
+ resolution_hint=f"Valid transitions: {[s.value for s in VALID_TRANSITIONS.get(self.current_state, set())]}",
+ )
+
+ # Record transition
+ transition = StateTransition(
+ from_state=self.current_state,
+ to_state=new_state,
+ timestamp=datetime.now(timezone.utc).isoformat(),
+ actor=actor,
+ reason=reason,
+ metadata=metadata or {},
+ )
+ self.transitions.append(transition)
+ self.current_state = new_state
+ self.updated_at = datetime.now(timezone.utc).isoformat()
+
+ return ConflictResult(has_conflict=False)
+
+ def check_auto_fix_allowed(self) -> ConflictResult:
+ """Check if auto-fix is allowed for this issue."""
+ # Check if in blocking state
+ if self.current_state in IssueLifecycleState.blocks_auto_fix():
+ return ConflictResult(
+ has_conflict=True,
+ conflict_type=ConflictType.BLOCKED_BY_CLASSIFICATION,
+ message=f"Auto-fix blocked: issue is marked as {self.current_state.value}",
+ blocking_state=self.current_state,
+ resolution_hint="Override classification to enable auto-fix",
+ )
+
+ # Check if triage required
+ if self.current_state in IssueLifecycleState.requires_triage_first():
+ return ConflictResult(
+ has_conflict=True,
+ conflict_type=ConflictType.TRIAGE_REQUIRED,
+ message="Triage required before auto-fix",
+ blocking_state=self.current_state,
+ resolution_hint="Run triage first",
+ )
+
+ return ConflictResult(has_conflict=False)
+
+ def check_pr_review_required(self) -> ConflictResult:
+ """Check if PR review is required before human notification."""
+ if self.current_state == IssueLifecycleState.PR_CREATED:
+ # PR needs AI review before notifying humans
+ return ConflictResult(
+ has_conflict=True,
+ conflict_type=ConflictType.REVIEW_REQUIRED,
+ message="AI review required before human notification",
+ resolution_hint="Run AI review on the PR",
+ )
+
+ return ConflictResult(has_conflict=False)
+
+ def acquire_lock(self, component: str) -> bool:
+ """Try to acquire lock for a component."""
+ if self.locked_by is not None:
+ return False
+ self.locked_by = component
+ self.locked_at = datetime.now(timezone.utc).isoformat()
+ return True
+
+ def release_lock(self, component: str) -> bool:
+ """Release lock held by a component."""
+ if self.locked_by != component:
+ return False
+ self.locked_by = None
+ self.locked_at = None
+ return True
+
+ def is_locked(self) -> bool:
+ """Check if issue is locked."""
+ return self.locked_by is not None
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "issue_number": self.issue_number,
+ "repo": self.repo,
+ "current_state": self.current_state.value,
+ "triage_result": self.triage_result,
+ "spec_id": self.spec_id,
+ "pr_number": self.pr_number,
+ "transitions": [t.to_dict() for t in self.transitions],
+ "locked_by": self.locked_by,
+ "locked_at": self.locked_at,
+ "created_at": self.created_at,
+ "updated_at": self.updated_at,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict[str, Any]) -> IssueLifecycle:
+ return cls(
+ issue_number=data["issue_number"],
+ repo=data["repo"],
+ current_state=IssueLifecycleState(data.get("current_state", "new")),
+ triage_result=data.get("triage_result"),
+ spec_id=data.get("spec_id"),
+ pr_number=data.get("pr_number"),
+ transitions=[
+ StateTransition.from_dict(t) for t in data.get("transitions", [])
+ ],
+ locked_by=data.get("locked_by"),
+ locked_at=data.get("locked_at"),
+ created_at=data.get("created_at", datetime.now(timezone.utc).isoformat()),
+ updated_at=data.get("updated_at", datetime.now(timezone.utc).isoformat()),
+ )
+
+
+class LifecycleManager:
+ """
+ Manages issue lifecycles and resolves conflicts.
+
+ Usage:
+ lifecycle = LifecycleManager(state_dir=Path(".auto-claude/github"))
+
+ # Get or create lifecycle for issue
+ state = lifecycle.get_or_create(repo="owner/repo", issue_number=123)
+
+ # Check if auto-fix is allowed
+ conflict = state.check_auto_fix_allowed()
+ if conflict.has_conflict:
+ print(f"Blocked: {conflict.message}")
+ return
+
+ # Transition state
+ result = lifecycle.transition(
+ repo="owner/repo",
+ issue_number=123,
+ new_state=IssueLifecycleState.BUILDING,
+ actor="automation",
+ )
+ """
+
+ def __init__(self, state_dir: Path):
+ self.state_dir = state_dir
+ self.lifecycle_dir = state_dir / "lifecycle"
+ self.lifecycle_dir.mkdir(parents=True, exist_ok=True)
+
+ def _get_file(self, repo: str, issue_number: int) -> Path:
+ safe_repo = repo.replace("/", "_")
+ return self.lifecycle_dir / f"{safe_repo}_{issue_number}.json"
+
+ def get(self, repo: str, issue_number: int) -> IssueLifecycle | None:
+ """Get lifecycle for an issue."""
+ file = self._get_file(repo, issue_number)
+ if not file.exists():
+ return None
+
+ with open(file) as f:
+ data = json.load(f)
+ return IssueLifecycle.from_dict(data)
+
+ def get_or_create(self, repo: str, issue_number: int) -> IssueLifecycle:
+ """Get or create lifecycle for an issue."""
+ lifecycle = self.get(repo, issue_number)
+ if lifecycle:
+ return lifecycle
+
+ lifecycle = IssueLifecycle(issue_number=issue_number, repo=repo)
+ self.save(lifecycle)
+ return lifecycle
+
+ def save(self, lifecycle: IssueLifecycle) -> None:
+ """Save lifecycle state."""
+ file = self._get_file(lifecycle.repo, lifecycle.issue_number)
+ with open(file, "w") as f:
+ json.dump(lifecycle.to_dict(), f, indent=2)
+
+ def transition(
+ self,
+ repo: str,
+ issue_number: int,
+ new_state: IssueLifecycleState,
+ actor: str,
+ reason: str | None = None,
+ metadata: dict[str, Any] | None = None,
+ ) -> ConflictResult:
+ """Transition issue to new state."""
+ lifecycle = self.get_or_create(repo, issue_number)
+ result = lifecycle.transition(new_state, actor, reason, metadata)
+
+ if not result.has_conflict:
+ self.save(lifecycle)
+
+ return result
+
+ def check_conflict(
+ self,
+ repo: str,
+ issue_number: int,
+ operation: str,
+ ) -> ConflictResult:
+ """Check for conflicts before an operation."""
+ lifecycle = self.get_or_create(repo, issue_number)
+
+ # Check lock
+ if lifecycle.is_locked():
+ return ConflictResult(
+ has_conflict=True,
+ conflict_type=ConflictType.CONCURRENT_OPERATION,
+ message=f"Issue locked by {lifecycle.locked_by}",
+ resolution_hint="Wait for current operation to complete",
+ )
+
+ # Operation-specific checks
+ if operation == "auto_fix":
+ return lifecycle.check_auto_fix_allowed()
+ elif operation == "notify_human":
+ return lifecycle.check_pr_review_required()
+
+ return ConflictResult(has_conflict=False)
+
+ def acquire_lock(
+ self,
+ repo: str,
+ issue_number: int,
+ component: str,
+ ) -> bool:
+ """Acquire lock for an issue."""
+ lifecycle = self.get_or_create(repo, issue_number)
+ if lifecycle.acquire_lock(component):
+ self.save(lifecycle)
+ return True
+ return False
+
+ def release_lock(
+ self,
+ repo: str,
+ issue_number: int,
+ component: str,
+ ) -> bool:
+ """Release lock for an issue."""
+ lifecycle = self.get(repo, issue_number)
+ if lifecycle and lifecycle.release_lock(component):
+ self.save(lifecycle)
+ return True
+ return False
+
+ def get_all_in_state(
+ self,
+ repo: str,
+ state: IssueLifecycleState,
+ ) -> list[IssueLifecycle]:
+ """Get all issues in a specific state."""
+ results = []
+ safe_repo = repo.replace("/", "_")
+
+ for file in self.lifecycle_dir.glob(f"{safe_repo}_*.json"):
+ with open(file) as f:
+ data = json.load(f)
+ lifecycle = IssueLifecycle.from_dict(data)
+ if lifecycle.current_state == state:
+ results.append(lifecycle)
+
+ return results
+
+ def get_summary(self, repo: str) -> dict[str, int]:
+ """Get count of issues by state."""
+ counts: dict[str, int] = {}
+ safe_repo = repo.replace("/", "_")
+
+ for file in self.lifecycle_dir.glob(f"{safe_repo}_*.json"):
+ with open(file) as f:
+ data = json.load(f)
+ state = data.get("current_state", "new")
+ counts[state] = counts.get(state, 0) + 1
+
+ return counts
diff --git a/apps/backend/runners/github/memory_integration.py b/apps/backend/runners/github/memory_integration.py
new file mode 100644
index 00000000..e088c547
--- /dev/null
+++ b/apps/backend/runners/github/memory_integration.py
@@ -0,0 +1,601 @@
+"""
+Memory Integration for GitHub Automation
+=========================================
+
+Connects the GitHub automation system to the existing Graphiti memory layer for:
+- Cross-session context retrieval
+- Historical pattern recognition
+- Codebase gotchas and quirks
+- Similar past reviews and their outcomes
+
+Leverages the existing Graphiti infrastructure from:
+- integrations/graphiti/memory.py
+- integrations/graphiti/queries_pkg/graphiti.py
+- memory/graphiti_helpers.py
+
+Usage:
+ memory = GitHubMemoryIntegration(repo="owner/repo", state_dir=Path("..."))
+
+ # Before reviewing, get relevant context
+ context = await memory.get_review_context(
+ file_paths=["auth.py", "utils.py"],
+ change_description="Adding OAuth support",
+ )
+
+ # After review, store insights
+ await memory.store_review_insight(
+ pr_number=123,
+ file_paths=["auth.py"],
+ insight="Auth module requires careful session handling",
+ category="gotcha",
+ )
+"""
+
+from __future__ import annotations
+
+import json
+import sys
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+
+# Add parent paths to sys.path for imports
+_backend_dir = Path(__file__).parent.parent.parent
+if str(_backend_dir) not in sys.path:
+ sys.path.insert(0, str(_backend_dir))
+
+# Import Graphiti components
+try:
+ from integrations.graphiti.memory import (
+ GraphitiMemory,
+ GroupIdMode,
+ get_graphiti_memory,
+ is_graphiti_enabled,
+ )
+ from memory.graphiti_helpers import is_graphiti_memory_enabled
+
+ GRAPHITI_AVAILABLE = True
+except (ImportError, ValueError, SystemError):
+ GRAPHITI_AVAILABLE = False
+
+ def is_graphiti_enabled() -> bool:
+ return False
+
+ def is_graphiti_memory_enabled() -> bool:
+ return False
+
+ GroupIdMode = None
+
+
+@dataclass
+class MemoryHint:
+ """
+ A hint from memory to aid decision making.
+ """
+
+ hint_type: str # gotcha, pattern, warning, context
+ content: str
+ relevance_score: float = 0.0
+ source: str = "memory"
+ metadata: dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass
+class ReviewContext:
+ """
+ Context gathered from memory for a code review.
+ """
+
+ # Past insights about affected files
+ file_insights: list[MemoryHint] = field(default_factory=list)
+
+ # Similar past changes and their outcomes
+ similar_changes: list[dict[str, Any]] = field(default_factory=list)
+
+ # Known gotchas for this area
+ gotchas: list[MemoryHint] = field(default_factory=list)
+
+ # Codebase patterns relevant to this review
+ patterns: list[MemoryHint] = field(default_factory=list)
+
+ # Historical context from past reviews
+ past_reviews: list[dict[str, Any]] = field(default_factory=list)
+
+ @property
+ def has_context(self) -> bool:
+ return bool(
+ self.file_insights
+ or self.similar_changes
+ or self.gotchas
+ or self.patterns
+ or self.past_reviews
+ )
+
+ def to_prompt_section(self) -> str:
+ """Format memory context for inclusion in prompts."""
+ if not self.has_context:
+ return ""
+
+ sections = []
+
+ if self.gotchas:
+ sections.append("### Known Gotchas")
+ for gotcha in self.gotchas:
+ sections.append(f"- {gotcha.content}")
+
+ if self.file_insights:
+ sections.append("\n### File Insights")
+ for insight in self.file_insights:
+ sections.append(f"- {insight.content}")
+
+ if self.patterns:
+ sections.append("\n### Codebase Patterns")
+ for pattern in self.patterns:
+ sections.append(f"- {pattern.content}")
+
+ if self.similar_changes:
+ sections.append("\n### Similar Past Changes")
+ for change in self.similar_changes[:3]:
+ outcome = change.get("outcome", "unknown")
+ desc = change.get("description", "")
+ sections.append(f"- {desc} (outcome: {outcome})")
+
+ if self.past_reviews:
+ sections.append("\n### Past Review Notes")
+ for review in self.past_reviews[:3]:
+ note = review.get("note", "")
+ pr = review.get("pr_number", "")
+ sections.append(f"- PR #{pr}: {note}")
+
+ return "\n".join(sections)
+
+
+class GitHubMemoryIntegration:
+ """
+ Integrates GitHub automation with the existing Graphiti memory layer.
+
+ Uses the project's Graphiti infrastructure for:
+ - Storing review outcomes and insights
+ - Retrieving relevant context from past sessions
+ - Recording patterns and gotchas discovered during reviews
+ """
+
+ def __init__(
+ self,
+ repo: str,
+ state_dir: Path | None = None,
+ project_dir: Path | None = None,
+ ):
+ """
+ Initialize memory integration.
+
+ Args:
+ repo: Repository identifier (owner/repo)
+ state_dir: Local state directory for the GitHub runner
+ project_dir: Project root directory (for Graphiti namespacing)
+ """
+ self.repo = repo
+ self.state_dir = state_dir or Path(".auto-claude/github")
+ self.project_dir = project_dir or Path.cwd()
+ self.memory_dir = self.state_dir / "memory"
+ self.memory_dir.mkdir(parents=True, exist_ok=True)
+
+ # Graphiti memory instance (lazy-loaded)
+ self._graphiti: GraphitiMemory | None = None
+
+ # Local cache for insights (fallback when Graphiti not available)
+ self._local_insights: list[dict[str, Any]] = []
+ self._load_local_insights()
+
+ def _load_local_insights(self) -> None:
+ """Load locally stored insights."""
+ insights_file = self.memory_dir / f"{self.repo.replace('/', '_')}_insights.json"
+ if insights_file.exists():
+ try:
+ with open(insights_file) as f:
+ self._local_insights = json.load(f).get("insights", [])
+ except (json.JSONDecodeError, KeyError):
+ self._local_insights = []
+
+ def _save_local_insights(self) -> None:
+ """Save insights locally."""
+ insights_file = self.memory_dir / f"{self.repo.replace('/', '_')}_insights.json"
+ with open(insights_file, "w") as f:
+ json.dump(
+ {
+ "repo": self.repo,
+ "updated_at": datetime.now(timezone.utc).isoformat(),
+ "insights": self._local_insights[-1000:], # Keep last 1000
+ },
+ f,
+ indent=2,
+ )
+
+ @property
+ def is_enabled(self) -> bool:
+ """Check if Graphiti memory integration is available."""
+ return GRAPHITI_AVAILABLE and is_graphiti_memory_enabled()
+
+ async def _get_graphiti(self) -> GraphitiMemory | None:
+ """Get or create Graphiti memory instance."""
+ if not self.is_enabled:
+ return None
+
+ if self._graphiti is None:
+ try:
+ # Create spec dir for GitHub automation
+ spec_dir = self.state_dir / "graphiti" / self.repo.replace("/", "_")
+ spec_dir.mkdir(parents=True, exist_ok=True)
+
+ self._graphiti = get_graphiti_memory(
+ spec_dir=spec_dir,
+ project_dir=self.project_dir,
+ group_id_mode=GroupIdMode.PROJECT, # Share context across all GitHub reviews
+ )
+
+ # Initialize
+ await self._graphiti.initialize()
+
+ except Exception as e:
+ self._graphiti = None
+ return None
+
+ return self._graphiti
+
+ async def get_review_context(
+ self,
+ file_paths: list[str],
+ change_description: str,
+ pr_number: int | None = None,
+ ) -> ReviewContext:
+ """
+ Get context from memory for a code review.
+
+ Args:
+ file_paths: Files being changed
+ change_description: Description of the changes
+ pr_number: PR number if available
+
+ Returns:
+ ReviewContext with relevant memory hints
+ """
+ context = ReviewContext()
+
+ # Query Graphiti if available
+ graphiti = await self._get_graphiti()
+ if graphiti:
+ try:
+ # Query for file-specific insights
+ for file_path in file_paths[:5]: # Limit to 5 files
+ results = await graphiti.get_relevant_context(
+ query=f"What should I know about {file_path}?",
+ num_results=3,
+ include_project_context=True,
+ )
+ for result in results:
+ content = result.get("content") or result.get("summary", "")
+ if content:
+ context.file_insights.append(
+ MemoryHint(
+ hint_type="file_insight",
+ content=content,
+ relevance_score=result.get("score", 0.5),
+ source="graphiti",
+ metadata=result,
+ )
+ )
+
+ # Query for similar changes
+ similar = await graphiti.get_similar_task_outcomes(
+ task_description=f"PR review: {change_description}",
+ limit=5,
+ )
+ for item in similar:
+ context.similar_changes.append(
+ {
+ "description": item.get("description", ""),
+ "outcome": "success" if item.get("success") else "failed",
+ "task_id": item.get("task_id"),
+ }
+ )
+
+ # Get session history for recent gotchas
+ history = await graphiti.get_session_history(limit=10, spec_only=False)
+ for session in history:
+ discoveries = session.get("discoveries", {})
+ for gotcha in discoveries.get("gotchas_encountered", []):
+ context.gotchas.append(
+ MemoryHint(
+ hint_type="gotcha",
+ content=gotcha,
+ relevance_score=0.7,
+ source="graphiti",
+ )
+ )
+ for pattern in discoveries.get("patterns_found", []):
+ context.patterns.append(
+ MemoryHint(
+ hint_type="pattern",
+ content=pattern,
+ relevance_score=0.6,
+ source="graphiti",
+ )
+ )
+
+ except Exception:
+ # Graphiti failed, fall through to local
+ pass
+
+ # Add local insights
+ for insight in self._local_insights:
+ # Match by file path
+ if any(f in insight.get("file_paths", []) for f in file_paths):
+ if insight.get("category") == "gotcha":
+ context.gotchas.append(
+ MemoryHint(
+ hint_type="gotcha",
+ content=insight.get("content", ""),
+ relevance_score=0.7,
+ source="local",
+ )
+ )
+ elif insight.get("category") == "pattern":
+ context.patterns.append(
+ MemoryHint(
+ hint_type="pattern",
+ content=insight.get("content", ""),
+ relevance_score=0.6,
+ source="local",
+ )
+ )
+
+ return context
+
+ async def store_review_insight(
+ self,
+ pr_number: int,
+ file_paths: list[str],
+ insight: str,
+ category: str = "insight",
+ severity: str = "info",
+ ) -> None:
+ """
+ Store an insight from a review for future reference.
+
+ Args:
+ pr_number: PR number
+ file_paths: Files involved
+ insight: The insight to store
+ category: Category (gotcha, pattern, warning, insight)
+ severity: Severity level
+ """
+ now = datetime.now(timezone.utc)
+
+ # Store locally
+ self._local_insights.append(
+ {
+ "pr_number": pr_number,
+ "file_paths": file_paths,
+ "content": insight,
+ "category": category,
+ "severity": severity,
+ "created_at": now.isoformat(),
+ }
+ )
+ self._save_local_insights()
+
+ # Store in Graphiti if available
+ graphiti = await self._get_graphiti()
+ if graphiti:
+ try:
+ if category == "gotcha":
+ await graphiti.save_gotcha(
+ f"[{self.repo}] PR #{pr_number}: {insight}"
+ )
+ elif category == "pattern":
+ await graphiti.save_pattern(
+ f"[{self.repo}] PR #{pr_number}: {insight}"
+ )
+ else:
+ # Save as session insight
+ await graphiti.save_session_insights(
+ session_num=pr_number,
+ insights={
+ "type": "github_review_insight",
+ "repo": self.repo,
+ "pr_number": pr_number,
+ "file_paths": file_paths,
+ "content": insight,
+ "category": category,
+ "severity": severity,
+ },
+ )
+ except Exception:
+ # Graphiti failed, local storage is backup
+ pass
+
+ async def store_review_outcome(
+ self,
+ pr_number: int,
+ prediction: str,
+ outcome: str,
+ was_correct: bool,
+ notes: str | None = None,
+ ) -> None:
+ """
+ Store the outcome of a review for learning.
+
+ Args:
+ pr_number: PR number
+ prediction: What the system predicted
+ outcome: What actually happened
+ was_correct: Whether prediction was correct
+ notes: Additional notes
+ """
+ now = datetime.now(timezone.utc)
+
+ # Store locally
+ self._local_insights.append(
+ {
+ "pr_number": pr_number,
+ "content": f"PR #{pr_number}: Predicted {prediction}, got {outcome}. {'Correct' if was_correct else 'Incorrect'}. {notes or ''}",
+ "category": "outcome",
+ "prediction": prediction,
+ "outcome": outcome,
+ "was_correct": was_correct,
+ "created_at": now.isoformat(),
+ }
+ )
+ self._save_local_insights()
+
+ # Store in Graphiti
+ graphiti = await self._get_graphiti()
+ if graphiti:
+ try:
+ await graphiti.save_task_outcome(
+ task_id=f"github_review_{self.repo}_{pr_number}",
+ success=was_correct,
+ outcome=f"Predicted {prediction}, actual {outcome}",
+ metadata={
+ "type": "github_review",
+ "repo": self.repo,
+ "pr_number": pr_number,
+ "prediction": prediction,
+ "actual_outcome": outcome,
+ "notes": notes,
+ },
+ )
+ except Exception:
+ pass
+
+ async def get_codebase_patterns(
+ self,
+ area: str | None = None,
+ ) -> list[MemoryHint]:
+ """
+ Get known codebase patterns.
+
+ Args:
+ area: Specific area (e.g., "auth", "api", "database")
+
+ Returns:
+ List of pattern hints
+ """
+ patterns = []
+
+ graphiti = await self._get_graphiti()
+ if graphiti:
+ try:
+ query = (
+ f"Codebase patterns for {area}"
+ if area
+ else "Codebase patterns and conventions"
+ )
+ results = await graphiti.get_relevant_context(
+ query=query,
+ num_results=10,
+ include_project_context=True,
+ )
+ for result in results:
+ content = result.get("content") or result.get("summary", "")
+ if content:
+ patterns.append(
+ MemoryHint(
+ hint_type="pattern",
+ content=content,
+ relevance_score=result.get("score", 0.5),
+ source="graphiti",
+ )
+ )
+ except Exception:
+ pass
+
+ # Add local patterns
+ for insight in self._local_insights:
+ if insight.get("category") == "pattern":
+ if not area or area.lower() in insight.get("content", "").lower():
+ patterns.append(
+ MemoryHint(
+ hint_type="pattern",
+ content=insight.get("content", ""),
+ relevance_score=0.6,
+ source="local",
+ )
+ )
+
+ return patterns
+
+ async def explain_finding(
+ self,
+ finding_id: str,
+ finding_description: str,
+ file_path: str,
+ ) -> str | None:
+ """
+ Get memory-backed explanation for a finding.
+
+ Answers "Why did you flag this?" with historical context.
+
+ Args:
+ finding_id: Finding identifier
+ finding_description: What was found
+ file_path: File where it was found
+
+ Returns:
+ Explanation with historical context, or None
+ """
+ graphiti = await self._get_graphiti()
+ if not graphiti:
+ return None
+
+ try:
+ results = await graphiti.get_relevant_context(
+ query=f"Why flag: {finding_description} in {file_path}",
+ num_results=3,
+ include_project_context=True,
+ )
+
+ if results:
+ explanations = []
+ for result in results:
+ content = result.get("content") or result.get("summary", "")
+ if content:
+ explanations.append(f"- {content}")
+
+ if explanations:
+ return "Historical context:\n" + "\n".join(explanations)
+
+ except Exception:
+ pass
+
+ return None
+
+ async def close(self) -> None:
+ """Close Graphiti connection."""
+ if self._graphiti:
+ try:
+ await self._graphiti.close()
+ except Exception:
+ pass
+ self._graphiti = None
+
+ def get_summary(self) -> dict[str, Any]:
+ """Get summary of stored memory."""
+ categories = {}
+ for insight in self._local_insights:
+ cat = insight.get("category", "unknown")
+ categories[cat] = categories.get(cat, 0) + 1
+
+ graphiti_status = None
+ if self._graphiti:
+ graphiti_status = self._graphiti.get_status_summary()
+
+ return {
+ "repo": self.repo,
+ "total_local_insights": len(self._local_insights),
+ "by_category": categories,
+ "graphiti_available": GRAPHITI_AVAILABLE,
+ "graphiti_enabled": self.is_enabled,
+ "graphiti_status": graphiti_status,
+ }
diff --git a/apps/backend/runners/github/models.py b/apps/backend/runners/github/models.py
new file mode 100644
index 00000000..709e702a
--- /dev/null
+++ b/apps/backend/runners/github/models.py
@@ -0,0 +1,851 @@
+"""
+GitHub Automation Data Models
+=============================
+
+Data structures for GitHub automation features.
+Stored in .auto-claude/github/pr/ and .auto-claude/github/issues/
+
+All save() operations use file locking to prevent corruption in concurrent scenarios.
+"""
+
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass, field
+from datetime import datetime
+from enum import Enum
+from pathlib import Path
+
+try:
+ from .file_lock import locked_json_update, locked_json_write
+except (ImportError, ValueError, SystemError):
+ from file_lock import locked_json_update, locked_json_write
+
+
+class ReviewSeverity(str, Enum):
+ """Severity levels for PR review findings."""
+
+ CRITICAL = "critical"
+ HIGH = "high"
+ MEDIUM = "medium"
+ LOW = "low"
+
+
+class ReviewCategory(str, Enum):
+ """Categories for PR review findings."""
+
+ SECURITY = "security"
+ QUALITY = "quality"
+ STYLE = "style"
+ TEST = "test"
+ DOCS = "docs"
+ PATTERN = "pattern"
+ PERFORMANCE = "performance"
+ VERIFICATION_FAILED = "verification_failed" # NEW: Cannot verify requirements/paths
+ REDUNDANCY = "redundancy" # NEW: Duplicate code/logic detected
+
+
+class ReviewPass(str, Enum):
+ """Multi-pass review stages."""
+
+ QUICK_SCAN = "quick_scan"
+ SECURITY = "security"
+ QUALITY = "quality"
+ DEEP_ANALYSIS = "deep_analysis"
+ STRUCTURAL = "structural" # Feature creep, architecture, PR structure
+ AI_COMMENT_TRIAGE = "ai_comment_triage" # Verify other AI tool comments
+
+
+class MergeVerdict(str, Enum):
+ """Clear verdict for whether PR can be merged."""
+
+ READY_TO_MERGE = "ready_to_merge" # No blockers, good to go
+ MERGE_WITH_CHANGES = "merge_with_changes" # Minor issues, fix before merge
+ NEEDS_REVISION = "needs_revision" # Significant issues, needs rework
+ BLOCKED = "blocked" # Critical issues, cannot merge
+
+
+class AICommentVerdict(str, Enum):
+ """Verdict on AI tool comments (CodeRabbit, Cursor, Greptile, etc.)."""
+
+ CRITICAL = "critical" # Must be addressed before merge
+ IMPORTANT = "important" # Should be addressed
+ NICE_TO_HAVE = "nice_to_have" # Optional improvement
+ TRIVIAL = "trivial" # Can be ignored
+ FALSE_POSITIVE = "false_positive" # AI was wrong
+
+
+class TriageCategory(str, Enum):
+ """Issue triage categories."""
+
+ BUG = "bug"
+ FEATURE = "feature"
+ DOCUMENTATION = "documentation"
+ QUESTION = "question"
+ DUPLICATE = "duplicate"
+ SPAM = "spam"
+ FEATURE_CREEP = "feature_creep"
+
+
+class AutoFixStatus(str, Enum):
+ """Status for auto-fix operations."""
+
+ # Initial states
+ PENDING = "pending"
+ ANALYZING = "analyzing"
+
+ # Spec creation states
+ CREATING_SPEC = "creating_spec"
+ WAITING_APPROVAL = "waiting_approval" # P1-3: Human review gate
+
+ # Build states
+ BUILDING = "building"
+ QA_REVIEW = "qa_review"
+
+ # PR states
+ PR_CREATED = "pr_created"
+ MERGE_CONFLICT = "merge_conflict" # P1-3: Conflict resolution needed
+
+ # Terminal states
+ COMPLETED = "completed"
+ FAILED = "failed"
+ CANCELLED = "cancelled" # P1-3: User cancelled
+
+ # Special states
+ STALE = "stale" # P1-3: Issue updated after spec creation
+ RATE_LIMITED = "rate_limited" # P1-3: Waiting for rate limit reset
+
+ @classmethod
+ def terminal_states(cls) -> set[AutoFixStatus]:
+ """States that represent end of workflow."""
+ return {cls.COMPLETED, cls.FAILED, cls.CANCELLED}
+
+ @classmethod
+ def recoverable_states(cls) -> set[AutoFixStatus]:
+ """States that can be recovered from."""
+ return {cls.FAILED, cls.STALE, cls.RATE_LIMITED, cls.MERGE_CONFLICT}
+
+ @classmethod
+ def active_states(cls) -> set[AutoFixStatus]:
+ """States that indicate work in progress."""
+ return {
+ cls.PENDING,
+ cls.ANALYZING,
+ cls.CREATING_SPEC,
+ cls.BUILDING,
+ cls.QA_REVIEW,
+ cls.PR_CREATED,
+ }
+
+ def can_transition_to(self, new_state: AutoFixStatus) -> bool:
+ """Check if transition to new_state is valid."""
+ valid_transitions = {
+ AutoFixStatus.PENDING: {
+ AutoFixStatus.ANALYZING,
+ AutoFixStatus.CANCELLED,
+ },
+ AutoFixStatus.ANALYZING: {
+ AutoFixStatus.CREATING_SPEC,
+ AutoFixStatus.FAILED,
+ AutoFixStatus.CANCELLED,
+ AutoFixStatus.RATE_LIMITED,
+ },
+ AutoFixStatus.CREATING_SPEC: {
+ AutoFixStatus.WAITING_APPROVAL,
+ AutoFixStatus.BUILDING,
+ AutoFixStatus.FAILED,
+ AutoFixStatus.CANCELLED,
+ AutoFixStatus.STALE,
+ },
+ AutoFixStatus.WAITING_APPROVAL: {
+ AutoFixStatus.BUILDING,
+ AutoFixStatus.CANCELLED,
+ AutoFixStatus.STALE,
+ },
+ AutoFixStatus.BUILDING: {
+ AutoFixStatus.QA_REVIEW,
+ AutoFixStatus.FAILED,
+ AutoFixStatus.CANCELLED,
+ AutoFixStatus.RATE_LIMITED,
+ },
+ AutoFixStatus.QA_REVIEW: {
+ AutoFixStatus.PR_CREATED,
+ AutoFixStatus.BUILDING, # Fix loop
+ AutoFixStatus.FAILED,
+ AutoFixStatus.CANCELLED,
+ },
+ AutoFixStatus.PR_CREATED: {
+ AutoFixStatus.COMPLETED,
+ AutoFixStatus.MERGE_CONFLICT,
+ AutoFixStatus.FAILED,
+ },
+ AutoFixStatus.MERGE_CONFLICT: {
+ AutoFixStatus.BUILDING, # Retry after conflict resolution
+ AutoFixStatus.FAILED,
+ AutoFixStatus.CANCELLED,
+ },
+ AutoFixStatus.STALE: {
+ AutoFixStatus.ANALYZING, # Re-analyze with new issue content
+ AutoFixStatus.CANCELLED,
+ },
+ AutoFixStatus.RATE_LIMITED: {
+ AutoFixStatus.PENDING, # Resume after rate limit
+ AutoFixStatus.CANCELLED,
+ },
+ # Terminal states - no transitions
+ AutoFixStatus.COMPLETED: set(),
+ AutoFixStatus.FAILED: {AutoFixStatus.PENDING}, # Allow retry
+ AutoFixStatus.CANCELLED: set(),
+ }
+ return new_state in valid_transitions.get(self, set())
+
+
+@dataclass
+class PRReviewFinding:
+ """A single finding from a PR review."""
+
+ id: str
+ severity: ReviewSeverity
+ category: ReviewCategory
+ title: str
+ description: str
+ file: str
+ line: int
+ end_line: int | None = None
+ suggested_fix: str | None = None
+ fixable: bool = False
+ # NEW: Support for verification and redundancy detection
+ confidence: float = 0.85 # AI's confidence in this finding (0.0-1.0)
+ verification_note: str | None = (
+ None # What evidence is missing or couldn't be verified
+ )
+ redundant_with: str | None = None # Reference to duplicate code (file:line)
+
+ def to_dict(self) -> dict:
+ return {
+ "id": self.id,
+ "severity": self.severity.value,
+ "category": self.category.value,
+ "title": self.title,
+ "description": self.description,
+ "file": self.file,
+ "line": self.line,
+ "end_line": self.end_line,
+ "suggested_fix": self.suggested_fix,
+ "fixable": self.fixable,
+ # NEW fields
+ "confidence": self.confidence,
+ "verification_note": self.verification_note,
+ "redundant_with": self.redundant_with,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict) -> PRReviewFinding:
+ return cls(
+ id=data["id"],
+ severity=ReviewSeverity(data["severity"]),
+ category=ReviewCategory(data["category"]),
+ title=data["title"],
+ description=data["description"],
+ file=data["file"],
+ line=data["line"],
+ end_line=data.get("end_line"),
+ suggested_fix=data.get("suggested_fix"),
+ fixable=data.get("fixable", False),
+ # NEW fields
+ confidence=data.get("confidence", 0.85),
+ verification_note=data.get("verification_note"),
+ redundant_with=data.get("redundant_with"),
+ )
+
+
+@dataclass
+class AICommentTriage:
+ """Triage result for an AI tool comment (CodeRabbit, Cursor, Greptile, etc.)."""
+
+ comment_id: int
+ tool_name: str # "CodeRabbit", "Cursor", "Greptile", etc.
+ original_comment: str
+ verdict: AICommentVerdict
+ reasoning: str
+ response_comment: str | None = None # Comment to post in reply
+
+ def to_dict(self) -> dict:
+ return {
+ "comment_id": self.comment_id,
+ "tool_name": self.tool_name,
+ "original_comment": self.original_comment,
+ "verdict": self.verdict.value,
+ "reasoning": self.reasoning,
+ "response_comment": self.response_comment,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict) -> AICommentTriage:
+ return cls(
+ comment_id=data["comment_id"],
+ tool_name=data["tool_name"],
+ original_comment=data["original_comment"],
+ verdict=AICommentVerdict(data["verdict"]),
+ reasoning=data["reasoning"],
+ response_comment=data.get("response_comment"),
+ )
+
+
+@dataclass
+class StructuralIssue:
+ """Structural issue with the PR (feature creep, architecture, etc.)."""
+
+ id: str
+ issue_type: str # "feature_creep", "scope_creep", "architecture_violation", "poor_structure"
+ severity: ReviewSeverity
+ title: str
+ description: str
+ impact: str # Why this matters
+ suggestion: str # How to fix
+
+ def to_dict(self) -> dict:
+ return {
+ "id": self.id,
+ "issue_type": self.issue_type,
+ "severity": self.severity.value,
+ "title": self.title,
+ "description": self.description,
+ "impact": self.impact,
+ "suggestion": self.suggestion,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict) -> StructuralIssue:
+ return cls(
+ id=data["id"],
+ issue_type=data["issue_type"],
+ severity=ReviewSeverity(data["severity"]),
+ title=data["title"],
+ description=data["description"],
+ impact=data["impact"],
+ suggestion=data["suggestion"],
+ )
+
+
+@dataclass
+class PRReviewResult:
+ """Complete result of a PR review."""
+
+ pr_number: int
+ repo: str
+ success: bool
+ findings: list[PRReviewFinding] = field(default_factory=list)
+ summary: str = ""
+ overall_status: str = "comment" # approve, request_changes, comment
+ review_id: int | None = None
+ reviewed_at: str = field(default_factory=lambda: datetime.now().isoformat())
+ error: str | None = None
+
+ # NEW: Enhanced verdict system
+ verdict: MergeVerdict = MergeVerdict.READY_TO_MERGE
+ verdict_reasoning: str = ""
+ blockers: list[str] = field(default_factory=list) # Issues that MUST be fixed
+
+ # NEW: Risk assessment
+ risk_assessment: dict = field(
+ default_factory=lambda: {
+ "complexity": "low", # low, medium, high
+ "security_impact": "none", # none, low, medium, critical
+ "scope_coherence": "good", # good, mixed, poor
+ }
+ )
+
+ # NEW: Structural issues and AI comment triages
+ structural_issues: list[StructuralIssue] = field(default_factory=list)
+ ai_comment_triages: list[AICommentTriage] = field(default_factory=list)
+
+ # NEW: Quick scan summary preserved
+ quick_scan_summary: dict = field(default_factory=dict)
+
+ # Follow-up review tracking
+ reviewed_commit_sha: str | None = None # HEAD SHA at time of review
+ is_followup_review: bool = False # True if this is a follow-up review
+ previous_review_id: int | None = None # Reference to the review this follows up on
+ resolved_findings: list[str] = field(default_factory=list) # Finding IDs now fixed
+ unresolved_findings: list[str] = field(
+ default_factory=list
+ ) # Finding IDs still open
+ new_findings_since_last_review: list[str] = field(
+ default_factory=list
+ ) # New issues in recent commits
+
+ def to_dict(self) -> dict:
+ return {
+ "pr_number": self.pr_number,
+ "repo": self.repo,
+ "success": self.success,
+ "findings": [f.to_dict() for f in self.findings],
+ "summary": self.summary,
+ "overall_status": self.overall_status,
+ "review_id": self.review_id,
+ "reviewed_at": self.reviewed_at,
+ "error": self.error,
+ # NEW fields
+ "verdict": self.verdict.value,
+ "verdict_reasoning": self.verdict_reasoning,
+ "blockers": self.blockers,
+ "risk_assessment": self.risk_assessment,
+ "structural_issues": [s.to_dict() for s in self.structural_issues],
+ "ai_comment_triages": [t.to_dict() for t in self.ai_comment_triages],
+ "quick_scan_summary": self.quick_scan_summary,
+ # Follow-up review fields
+ "reviewed_commit_sha": self.reviewed_commit_sha,
+ "is_followup_review": self.is_followup_review,
+ "previous_review_id": self.previous_review_id,
+ "resolved_findings": self.resolved_findings,
+ "unresolved_findings": self.unresolved_findings,
+ "new_findings_since_last_review": self.new_findings_since_last_review,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict) -> PRReviewResult:
+ return cls(
+ pr_number=data["pr_number"],
+ repo=data["repo"],
+ success=data["success"],
+ findings=[PRReviewFinding.from_dict(f) for f in data.get("findings", [])],
+ summary=data.get("summary", ""),
+ overall_status=data.get("overall_status", "comment"),
+ review_id=data.get("review_id"),
+ reviewed_at=data.get("reviewed_at", datetime.now().isoformat()),
+ error=data.get("error"),
+ # NEW fields
+ verdict=MergeVerdict(data.get("verdict", "ready_to_merge")),
+ verdict_reasoning=data.get("verdict_reasoning", ""),
+ blockers=data.get("blockers", []),
+ risk_assessment=data.get(
+ "risk_assessment",
+ {
+ "complexity": "low",
+ "security_impact": "none",
+ "scope_coherence": "good",
+ },
+ ),
+ structural_issues=[
+ StructuralIssue.from_dict(s) for s in data.get("structural_issues", [])
+ ],
+ ai_comment_triages=[
+ AICommentTriage.from_dict(t) for t in data.get("ai_comment_triages", [])
+ ],
+ quick_scan_summary=data.get("quick_scan_summary", {}),
+ # Follow-up review fields
+ reviewed_commit_sha=data.get("reviewed_commit_sha"),
+ is_followup_review=data.get("is_followup_review", False),
+ previous_review_id=data.get("previous_review_id"),
+ resolved_findings=data.get("resolved_findings", []),
+ unresolved_findings=data.get("unresolved_findings", []),
+ new_findings_since_last_review=data.get(
+ "new_findings_since_last_review", []
+ ),
+ )
+
+ async def save(self, github_dir: Path) -> None:
+ """Save review result to .auto-claude/github/pr/ with file locking."""
+ pr_dir = github_dir / "pr"
+ pr_dir.mkdir(parents=True, exist_ok=True)
+
+ review_file = pr_dir / f"review_{self.pr_number}.json"
+
+ # Atomic locked write
+ await locked_json_write(review_file, self.to_dict(), timeout=5.0)
+
+ # Update index with locking
+ await self._update_index(pr_dir)
+
+ async def _update_index(self, pr_dir: Path) -> None:
+ """Update the PR review index with file locking."""
+ index_file = pr_dir / "index.json"
+
+ def update_index(current_data):
+ """Update function for atomic index update."""
+ if current_data is None:
+ current_data = {"reviews": [], "last_updated": None}
+
+ # Update or add entry
+ reviews = current_data.get("reviews", [])
+ existing = next(
+ (r for r in reviews if r["pr_number"] == self.pr_number), None
+ )
+
+ entry = {
+ "pr_number": self.pr_number,
+ "repo": self.repo,
+ "overall_status": self.overall_status,
+ "findings_count": len(self.findings),
+ "reviewed_at": self.reviewed_at,
+ }
+
+ if existing:
+ reviews = [
+ entry if r["pr_number"] == self.pr_number else r for r in reviews
+ ]
+ else:
+ reviews.append(entry)
+
+ current_data["reviews"] = reviews
+ current_data["last_updated"] = datetime.now().isoformat()
+
+ return current_data
+
+ # Atomic locked update
+ await locked_json_update(index_file, update_index, timeout=5.0)
+
+ @classmethod
+ def load(cls, github_dir: Path, pr_number: int) -> PRReviewResult | None:
+ """Load a review result from disk."""
+ review_file = github_dir / "pr" / f"review_{pr_number}.json"
+ if not review_file.exists():
+ return None
+
+ with open(review_file) as f:
+ return cls.from_dict(json.load(f))
+
+
+@dataclass
+class FollowupReviewContext:
+ """Context for a follow-up review."""
+
+ pr_number: int
+ previous_review: PRReviewResult
+ previous_commit_sha: str
+ current_commit_sha: str
+
+ # Changes since last review
+ commits_since_review: list[dict] = field(default_factory=list)
+ files_changed_since_review: list[str] = field(default_factory=list)
+ diff_since_review: str = ""
+
+ # Comments since last review
+ contributor_comments_since_review: list[dict] = field(default_factory=list)
+ ai_bot_comments_since_review: list[dict] = field(default_factory=list)
+
+
+@dataclass
+class TriageResult:
+ """Result of triaging a single issue."""
+
+ issue_number: int
+ repo: str
+ category: TriageCategory
+ confidence: float # 0.0 to 1.0
+ labels_to_add: list[str] = field(default_factory=list)
+ labels_to_remove: list[str] = field(default_factory=list)
+ is_duplicate: bool = False
+ duplicate_of: int | None = None
+ is_spam: bool = False
+ is_feature_creep: bool = False
+ suggested_breakdown: list[str] = field(default_factory=list)
+ priority: str = "medium" # high, medium, low
+ comment: str | None = None
+ triaged_at: str = field(default_factory=lambda: datetime.now().isoformat())
+
+ def to_dict(self) -> dict:
+ return {
+ "issue_number": self.issue_number,
+ "repo": self.repo,
+ "category": self.category.value,
+ "confidence": self.confidence,
+ "labels_to_add": self.labels_to_add,
+ "labels_to_remove": self.labels_to_remove,
+ "is_duplicate": self.is_duplicate,
+ "duplicate_of": self.duplicate_of,
+ "is_spam": self.is_spam,
+ "is_feature_creep": self.is_feature_creep,
+ "suggested_breakdown": self.suggested_breakdown,
+ "priority": self.priority,
+ "comment": self.comment,
+ "triaged_at": self.triaged_at,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict) -> TriageResult:
+ return cls(
+ issue_number=data["issue_number"],
+ repo=data["repo"],
+ category=TriageCategory(data["category"]),
+ confidence=data["confidence"],
+ labels_to_add=data.get("labels_to_add", []),
+ labels_to_remove=data.get("labels_to_remove", []),
+ is_duplicate=data.get("is_duplicate", False),
+ duplicate_of=data.get("duplicate_of"),
+ is_spam=data.get("is_spam", False),
+ is_feature_creep=data.get("is_feature_creep", False),
+ suggested_breakdown=data.get("suggested_breakdown", []),
+ priority=data.get("priority", "medium"),
+ comment=data.get("comment"),
+ triaged_at=data.get("triaged_at", datetime.now().isoformat()),
+ )
+
+ async def save(self, github_dir: Path) -> None:
+ """Save triage result to .auto-claude/github/issues/ with file locking."""
+ issues_dir = github_dir / "issues"
+ issues_dir.mkdir(parents=True, exist_ok=True)
+
+ triage_file = issues_dir / f"triage_{self.issue_number}.json"
+
+ # Atomic locked write
+ await locked_json_write(triage_file, self.to_dict(), timeout=5.0)
+
+ @classmethod
+ def load(cls, github_dir: Path, issue_number: int) -> TriageResult | None:
+ """Load a triage result from disk."""
+ triage_file = github_dir / "issues" / f"triage_{issue_number}.json"
+ if not triage_file.exists():
+ return None
+
+ with open(triage_file) as f:
+ return cls.from_dict(json.load(f))
+
+
+@dataclass
+class AutoFixState:
+ """State tracking for auto-fix operations."""
+
+ issue_number: int
+ issue_url: str
+ repo: str
+ status: AutoFixStatus = AutoFixStatus.PENDING
+ spec_id: str | None = None
+ spec_dir: str | None = None
+ pr_number: int | None = None
+ pr_url: str | None = None
+ bot_comments: list[str] = field(default_factory=list)
+ error: str | None = None
+ created_at: str = field(default_factory=lambda: datetime.now().isoformat())
+ updated_at: str = field(default_factory=lambda: datetime.now().isoformat())
+
+ def to_dict(self) -> dict:
+ return {
+ "issue_number": self.issue_number,
+ "issue_url": self.issue_url,
+ "repo": self.repo,
+ "status": self.status.value,
+ "spec_id": self.spec_id,
+ "spec_dir": self.spec_dir,
+ "pr_number": self.pr_number,
+ "pr_url": self.pr_url,
+ "bot_comments": self.bot_comments,
+ "error": self.error,
+ "created_at": self.created_at,
+ "updated_at": self.updated_at,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict) -> AutoFixState:
+ issue_number = data["issue_number"]
+ repo = data["repo"]
+ # Construct issue_url if missing (for backwards compatibility with old state files)
+ issue_url = (
+ data.get("issue_url") or f"https://github.com/{repo}/issues/{issue_number}"
+ )
+
+ return cls(
+ issue_number=issue_number,
+ issue_url=issue_url,
+ repo=repo,
+ status=AutoFixStatus(data.get("status", "pending")),
+ spec_id=data.get("spec_id"),
+ spec_dir=data.get("spec_dir"),
+ pr_number=data.get("pr_number"),
+ pr_url=data.get("pr_url"),
+ bot_comments=data.get("bot_comments", []),
+ error=data.get("error"),
+ created_at=data.get("created_at", datetime.now().isoformat()),
+ updated_at=data.get("updated_at", datetime.now().isoformat()),
+ )
+
+ def update_status(self, status: AutoFixStatus) -> None:
+ """Update status and timestamp with transition validation."""
+ if not self.status.can_transition_to(status):
+ raise ValueError(
+ f"Invalid state transition: {self.status.value} -> {status.value}"
+ )
+ self.status = status
+ self.updated_at = datetime.now().isoformat()
+
+ async def save(self, github_dir: Path) -> None:
+ """Save auto-fix state to .auto-claude/github/issues/ with file locking."""
+ issues_dir = github_dir / "issues"
+ issues_dir.mkdir(parents=True, exist_ok=True)
+
+ autofix_file = issues_dir / f"autofix_{self.issue_number}.json"
+
+ # Atomic locked write
+ await locked_json_write(autofix_file, self.to_dict(), timeout=5.0)
+
+ # Update index with locking
+ await self._update_index(issues_dir)
+
+ async def _update_index(self, issues_dir: Path) -> None:
+ """Update the issues index with auto-fix queue using file locking."""
+ index_file = issues_dir / "index.json"
+
+ def update_index(current_data):
+ """Update function for atomic index update."""
+ if current_data is None:
+ current_data = {
+ "triaged": [],
+ "auto_fix_queue": [],
+ "last_updated": None,
+ }
+
+ # Update auto-fix queue
+ queue = current_data.get("auto_fix_queue", [])
+ existing = next(
+ (q for q in queue if q["issue_number"] == self.issue_number), None
+ )
+
+ entry = {
+ "issue_number": self.issue_number,
+ "repo": self.repo,
+ "status": self.status.value,
+ "spec_id": self.spec_id,
+ "pr_number": self.pr_number,
+ "updated_at": self.updated_at,
+ }
+
+ if existing:
+ queue = [
+ entry if q["issue_number"] == self.issue_number else q
+ for q in queue
+ ]
+ else:
+ queue.append(entry)
+
+ current_data["auto_fix_queue"] = queue
+ current_data["last_updated"] = datetime.now().isoformat()
+
+ return current_data
+
+ # Atomic locked update
+ await locked_json_update(index_file, update_index, timeout=5.0)
+
+ @classmethod
+ def load(cls, github_dir: Path, issue_number: int) -> AutoFixState | None:
+ """Load an auto-fix state from disk."""
+ autofix_file = github_dir / "issues" / f"autofix_{issue_number}.json"
+ if not autofix_file.exists():
+ return None
+
+ with open(autofix_file) as f:
+ return cls.from_dict(json.load(f))
+
+
+@dataclass
+class GitHubRunnerConfig:
+ """Configuration for GitHub automation runners."""
+
+ # Authentication
+ token: str
+ repo: str # owner/repo format
+ bot_token: str | None = None # Separate bot account token
+
+ # Auto-fix settings
+ auto_fix_enabled: bool = False
+ auto_fix_labels: list[str] = field(default_factory=lambda: ["auto-fix"])
+ require_human_approval: bool = True
+
+ # Permission settings
+ auto_fix_allowed_roles: list[str] = field(
+ default_factory=lambda: ["OWNER", "MEMBER", "COLLABORATOR"]
+ )
+ allow_external_contributors: bool = False
+
+ # Triage settings
+ triage_enabled: bool = False
+ duplicate_threshold: float = 0.80
+ spam_threshold: float = 0.75
+ feature_creep_threshold: float = 0.70
+ enable_triage_comments: bool = False
+
+ # PR review settings
+ pr_review_enabled: bool = False
+ auto_post_reviews: bool = False
+ allow_fix_commits: bool = True
+ review_own_prs: bool = False # Whether bot can review its own PRs
+ use_orchestrator_review: bool = True # Use new Opus 4.5 orchestrating agent
+
+ # Model settings
+ model: str = "claude-sonnet-4-20250514"
+ thinking_level: str = "medium"
+
+ def to_dict(self) -> dict:
+ return {
+ "token": "***", # Never save token
+ "repo": self.repo,
+ "bot_token": "***" if self.bot_token else None,
+ "auto_fix_enabled": self.auto_fix_enabled,
+ "auto_fix_labels": self.auto_fix_labels,
+ "require_human_approval": self.require_human_approval,
+ "auto_fix_allowed_roles": self.auto_fix_allowed_roles,
+ "allow_external_contributors": self.allow_external_contributors,
+ "triage_enabled": self.triage_enabled,
+ "duplicate_threshold": self.duplicate_threshold,
+ "spam_threshold": self.spam_threshold,
+ "feature_creep_threshold": self.feature_creep_threshold,
+ "enable_triage_comments": self.enable_triage_comments,
+ "pr_review_enabled": self.pr_review_enabled,
+ "review_own_prs": self.review_own_prs,
+ "auto_post_reviews": self.auto_post_reviews,
+ "allow_fix_commits": self.allow_fix_commits,
+ "model": self.model,
+ "thinking_level": self.thinking_level,
+ }
+
+ def save_settings(self, github_dir: Path) -> None:
+ """Save non-sensitive settings to config.json."""
+ github_dir.mkdir(parents=True, exist_ok=True)
+ config_file = github_dir / "config.json"
+
+ # Save without tokens
+ settings = self.to_dict()
+ settings.pop("token", None)
+ settings.pop("bot_token", None)
+
+ with open(config_file, "w") as f:
+ json.dump(settings, f, indent=2)
+
+ @classmethod
+ def load_settings(
+ cls, github_dir: Path, token: str, repo: str, bot_token: str | None = None
+ ) -> GitHubRunnerConfig:
+ """Load settings from config.json, with tokens provided separately."""
+ config_file = github_dir / "config.json"
+
+ if config_file.exists():
+ with open(config_file) as f:
+ settings = json.load(f)
+ else:
+ settings = {}
+
+ return cls(
+ token=token,
+ repo=repo,
+ bot_token=bot_token,
+ auto_fix_enabled=settings.get("auto_fix_enabled", False),
+ auto_fix_labels=settings.get("auto_fix_labels", ["auto-fix"]),
+ require_human_approval=settings.get("require_human_approval", True),
+ auto_fix_allowed_roles=settings.get(
+ "auto_fix_allowed_roles", ["OWNER", "MEMBER", "COLLABORATOR"]
+ ),
+ allow_external_contributors=settings.get(
+ "allow_external_contributors", False
+ ),
+ triage_enabled=settings.get("triage_enabled", False),
+ duplicate_threshold=settings.get("duplicate_threshold", 0.80),
+ spam_threshold=settings.get("spam_threshold", 0.75),
+ feature_creep_threshold=settings.get("feature_creep_threshold", 0.70),
+ enable_triage_comments=settings.get("enable_triage_comments", False),
+ pr_review_enabled=settings.get("pr_review_enabled", False),
+ review_own_prs=settings.get("review_own_prs", False),
+ auto_post_reviews=settings.get("auto_post_reviews", False),
+ allow_fix_commits=settings.get("allow_fix_commits", True),
+ model=settings.get("model", "claude-sonnet-4-20250514"),
+ thinking_level=settings.get("thinking_level", "medium"),
+ )
diff --git a/apps/backend/runners/github/multi_repo.py b/apps/backend/runners/github/multi_repo.py
new file mode 100644
index 00000000..d0f531d4
--- /dev/null
+++ b/apps/backend/runners/github/multi_repo.py
@@ -0,0 +1,512 @@
+"""
+Multi-Repository Support
+========================
+
+Enables GitHub automation across multiple repositories with:
+- Per-repo configuration and state isolation
+- Path scoping for monorepos
+- Fork/upstream relationship detection
+- Cross-repo duplicate detection
+
+Usage:
+ # Configure multiple repos
+ config = MultiRepoConfig([
+ RepoConfig(repo="owner/frontend", path_scope="packages/frontend/*"),
+ RepoConfig(repo="owner/backend", path_scope="packages/backend/*"),
+ RepoConfig(repo="owner/shared"), # Full repo
+ ])
+
+ # Get isolated state for a repo
+ repo_state = config.get_repo_state("owner/frontend")
+"""
+
+from __future__ import annotations
+
+import fnmatch
+import json
+import re
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from enum import Enum
+from pathlib import Path
+from typing import Any
+
+
+class RepoRelationship(str, Enum):
+ """Relationship between repositories."""
+
+ STANDALONE = "standalone"
+ FORK = "fork"
+ UPSTREAM = "upstream"
+ MONOREPO_PACKAGE = "monorepo_package"
+
+
+@dataclass
+class RepoConfig:
+ """
+ Configuration for a single repository.
+
+ Attributes:
+ repo: Repository in owner/repo format
+ path_scope: Glob pattern to scope automation (for monorepos)
+ enabled: Whether automation is enabled for this repo
+ relationship: Relationship to other repos
+ upstream_repo: Upstream repo if this is a fork
+ labels: Label configuration overrides
+ trust_level: Trust level for this repo
+ """
+
+ repo: str # owner/repo format
+ path_scope: str | None = None # e.g., "packages/frontend/*"
+ enabled: bool = True
+ relationship: RepoRelationship = RepoRelationship.STANDALONE
+ upstream_repo: str | None = None
+ labels: dict[str, list[str]] = field(
+ default_factory=dict
+ ) # e.g., {"auto_fix": ["fix-me"]}
+ trust_level: int = 0 # 0-4 trust level
+ display_name: str | None = None # Human-readable name
+
+ # Feature toggles per repo
+ auto_fix_enabled: bool = True
+ pr_review_enabled: bool = True
+ triage_enabled: bool = True
+
+ def __post_init__(self):
+ if not self.display_name:
+ if self.path_scope:
+ # Use path scope for monorepo packages
+ self.display_name = f"{self.repo} ({self.path_scope})"
+ else:
+ self.display_name = self.repo
+
+ @property
+ def owner(self) -> str:
+ """Get repository owner."""
+ return self.repo.split("/")[0]
+
+ @property
+ def name(self) -> str:
+ """Get repository name."""
+ return self.repo.split("/")[1]
+
+ @property
+ def state_key(self) -> str:
+ """
+ Get unique key for state isolation.
+
+ For monorepos with path scopes, includes a hash of the scope.
+ """
+ if self.path_scope:
+ # Create a safe directory name from the scope
+ scope_safe = re.sub(r"[^\w-]", "_", self.path_scope)
+ return f"{self.repo.replace('/', '_')}_{scope_safe}"
+ return self.repo.replace("/", "_")
+
+ def matches_path(self, file_path: str) -> bool:
+ """
+ Check if a file path matches this repo's scope.
+
+ Args:
+ file_path: File path to check
+
+ Returns:
+ True if path matches scope (or no scope defined)
+ """
+ if not self.path_scope:
+ return True
+ return fnmatch.fnmatch(file_path, self.path_scope)
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "repo": self.repo,
+ "path_scope": self.path_scope,
+ "enabled": self.enabled,
+ "relationship": self.relationship.value,
+ "upstream_repo": self.upstream_repo,
+ "labels": self.labels,
+ "trust_level": self.trust_level,
+ "display_name": self.display_name,
+ "auto_fix_enabled": self.auto_fix_enabled,
+ "pr_review_enabled": self.pr_review_enabled,
+ "triage_enabled": self.triage_enabled,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict[str, Any]) -> RepoConfig:
+ return cls(
+ repo=data["repo"],
+ path_scope=data.get("path_scope"),
+ enabled=data.get("enabled", True),
+ relationship=RepoRelationship(data.get("relationship", "standalone")),
+ upstream_repo=data.get("upstream_repo"),
+ labels=data.get("labels", {}),
+ trust_level=data.get("trust_level", 0),
+ display_name=data.get("display_name"),
+ auto_fix_enabled=data.get("auto_fix_enabled", True),
+ pr_review_enabled=data.get("pr_review_enabled", True),
+ triage_enabled=data.get("triage_enabled", True),
+ )
+
+
+@dataclass
+class RepoState:
+ """
+ Isolated state for a repository.
+
+ Each repo has its own state directory to prevent conflicts.
+ """
+
+ config: RepoConfig
+ state_dir: Path
+ last_sync: str | None = None
+
+ @property
+ def pr_dir(self) -> Path:
+ """Directory for PR review state."""
+ d = self.state_dir / "pr"
+ d.mkdir(parents=True, exist_ok=True)
+ return d
+
+ @property
+ def issues_dir(self) -> Path:
+ """Directory for issue state."""
+ d = self.state_dir / "issues"
+ d.mkdir(parents=True, exist_ok=True)
+ return d
+
+ @property
+ def audit_dir(self) -> Path:
+ """Directory for audit logs."""
+ d = self.state_dir / "audit"
+ d.mkdir(parents=True, exist_ok=True)
+ return d
+
+
+class MultiRepoConfig:
+ """
+ Configuration manager for multiple repositories.
+
+ Handles:
+ - Multiple repo configurations
+ - State isolation per repo
+ - Fork/upstream relationship detection
+ - Cross-repo operations
+ """
+
+ def __init__(
+ self,
+ repos: list[RepoConfig] | None = None,
+ base_dir: Path | None = None,
+ ):
+ """
+ Initialize multi-repo configuration.
+
+ Args:
+ repos: List of repository configurations
+ base_dir: Base directory for all repo state
+ """
+ self.repos: dict[str, RepoConfig] = {}
+ self.base_dir = base_dir or Path(".auto-claude/github/repos")
+ self.base_dir.mkdir(parents=True, exist_ok=True)
+
+ if repos:
+ for repo in repos:
+ self.add_repo(repo)
+
+ def add_repo(self, config: RepoConfig) -> None:
+ """Add a repository configuration."""
+ self.repos[config.state_key] = config
+
+ def remove_repo(self, repo: str) -> bool:
+ """Remove a repository configuration."""
+ key = repo.replace("/", "_")
+ if key in self.repos:
+ del self.repos[key]
+ return True
+ return False
+
+ def get_repo(self, repo: str) -> RepoConfig | None:
+ """
+ Get configuration for a repository.
+
+ Args:
+ repo: Repository in owner/repo format
+
+ Returns:
+ RepoConfig if found, None otherwise
+ """
+ key = repo.replace("/", "_")
+ return self.repos.get(key)
+
+ def get_repo_for_path(self, repo: str, file_path: str) -> RepoConfig | None:
+ """
+ Get the most specific repo config for a file path.
+
+ Useful for monorepos where different packages have different configs.
+
+ Args:
+ repo: Repository in owner/repo format
+ file_path: File path within the repo
+
+ Returns:
+ Most specific matching RepoConfig
+ """
+ matches = []
+ for config in self.repos.values():
+ if config.repo != repo:
+ continue
+ if config.matches_path(file_path):
+ matches.append(config)
+
+ if not matches:
+ return None
+
+ # Return most specific (longest path scope)
+ return max(matches, key=lambda c: len(c.path_scope or ""))
+
+ def get_repo_state(self, repo: str) -> RepoState | None:
+ """
+ Get isolated state for a repository.
+
+ Args:
+ repo: Repository in owner/repo format
+
+ Returns:
+ RepoState with isolated directories
+ """
+ config = self.get_repo(repo)
+ if not config:
+ return None
+
+ state_dir = self.base_dir / config.state_key
+ state_dir.mkdir(parents=True, exist_ok=True)
+
+ return RepoState(
+ config=config,
+ state_dir=state_dir,
+ )
+
+ def list_repos(self, enabled_only: bool = True) -> list[RepoConfig]:
+ """
+ List all configured repositories.
+
+ Args:
+ enabled_only: Only return enabled repos
+
+ Returns:
+ List of RepoConfig objects
+ """
+ repos = list(self.repos.values())
+ if enabled_only:
+ repos = [r for r in repos if r.enabled]
+ return repos
+
+ def get_forks(self) -> dict[str, str]:
+ """
+ Get fork relationships.
+
+ Returns:
+ Dict mapping fork repo to upstream repo
+ """
+ return {
+ c.repo: c.upstream_repo
+ for c in self.repos.values()
+ if c.relationship == RepoRelationship.FORK and c.upstream_repo
+ }
+
+ def get_monorepo_packages(self, repo: str) -> list[RepoConfig]:
+ """
+ Get all packages in a monorepo.
+
+ Args:
+ repo: Base repository name
+
+ Returns:
+ List of RepoConfig for each package
+ """
+ return [
+ c
+ for c in self.repos.values()
+ if c.repo == repo
+ and c.relationship == RepoRelationship.MONOREPO_PACKAGE
+ and c.path_scope
+ ]
+
+ def save(self, config_file: Path | None = None) -> None:
+ """Save configuration to file."""
+ file_path = config_file or (self.base_dir / "multi_repo_config.json")
+ data = {
+ "repos": [c.to_dict() for c in self.repos.values()],
+ "last_updated": datetime.now(timezone.utc).isoformat(),
+ }
+ with open(file_path, "w") as f:
+ json.dump(data, f, indent=2)
+
+ @classmethod
+ def load(cls, config_file: Path) -> MultiRepoConfig:
+ """Load configuration from file."""
+ if not config_file.exists():
+ return cls()
+
+ with open(config_file) as f:
+ data = json.load(f)
+
+ repos = [RepoConfig.from_dict(r) for r in data.get("repos", [])]
+ return cls(repos=repos, base_dir=config_file.parent)
+
+
+class CrossRepoDetector:
+ """
+ Detects relationships and duplicates across repositories.
+ """
+
+ def __init__(self, config: MultiRepoConfig):
+ self.config = config
+
+ async def detect_fork_relationship(
+ self,
+ repo: str,
+ gh_client,
+ ) -> tuple[RepoRelationship, str | None]:
+ """
+ Detect if a repo is a fork and find its upstream.
+
+ Args:
+ repo: Repository to check
+ gh_client: GitHub client for API calls
+
+ Returns:
+ Tuple of (relationship, upstream_repo or None)
+ """
+ try:
+ repo_data = await gh_client.api_get(f"/repos/{repo}")
+
+ if repo_data.get("fork"):
+ parent = repo_data.get("parent", {})
+ upstream = parent.get("full_name")
+ if upstream:
+ return RepoRelationship.FORK, upstream
+
+ return RepoRelationship.STANDALONE, None
+
+ except Exception:
+ return RepoRelationship.STANDALONE, None
+
+ async def find_cross_repo_duplicates(
+ self,
+ issue_title: str,
+ issue_body: str,
+ source_repo: str,
+ gh_client,
+ ) -> list[dict[str, Any]]:
+ """
+ Find potential duplicate issues across configured repos.
+
+ Args:
+ issue_title: Issue title to search for
+ issue_body: Issue body
+ source_repo: Source repository
+ gh_client: GitHub client
+
+ Returns:
+ List of potential duplicate issues from other repos
+ """
+ duplicates = []
+
+ # Get related repos (same owner, forks, etc.)
+ related_repos = self._get_related_repos(source_repo)
+
+ for repo in related_repos:
+ try:
+ # Search for similar issues
+ query = f"repo:{repo} is:issue {issue_title}"
+ results = await gh_client.api_get(
+ "/search/issues",
+ params={"q": query, "per_page": 5},
+ )
+
+ for item in results.get("items", []):
+ if item.get("repository_url", "").endswith(source_repo):
+ continue # Skip same repo
+
+ duplicates.append(
+ {
+ "repo": repo,
+ "number": item["number"],
+ "title": item["title"],
+ "url": item["html_url"],
+ "state": item["state"],
+ }
+ )
+
+ except Exception:
+ continue
+
+ return duplicates
+
+ def _get_related_repos(self, source_repo: str) -> list[str]:
+ """Get repos related to the source (same owner, forks, etc.)."""
+ related = []
+ source_owner = source_repo.split("/")[0]
+
+ for config in self.config.repos.values():
+ if config.repo == source_repo:
+ continue
+
+ # Same owner
+ if config.owner == source_owner:
+ related.append(config.repo)
+ continue
+
+ # Fork relationship
+ if config.upstream_repo == source_repo:
+ related.append(config.repo)
+ elif (
+ config.repo == self.config.get_repo(source_repo).upstream_repo
+ if self.config.get_repo(source_repo)
+ else None
+ ):
+ related.append(config.repo)
+
+ return related
+
+
+# Convenience functions
+
+
+def create_monorepo_config(
+ repo: str,
+ packages: list[dict[str, str]],
+) -> list[RepoConfig]:
+ """
+ Create configs for a monorepo with multiple packages.
+
+ Args:
+ repo: Base repository name
+ packages: List of package definitions with name and path_scope
+
+ Returns:
+ List of RepoConfig for each package
+
+ Example:
+ configs = create_monorepo_config(
+ repo="owner/monorepo",
+ packages=[
+ {"name": "frontend", "path_scope": "packages/frontend/**"},
+ {"name": "backend", "path_scope": "packages/backend/**"},
+ {"name": "shared", "path_scope": "packages/shared/**"},
+ ],
+ )
+ """
+ configs = []
+ for pkg in packages:
+ configs.append(
+ RepoConfig(
+ repo=repo,
+ path_scope=pkg.get("path_scope"),
+ display_name=pkg.get("name", pkg.get("path_scope")),
+ relationship=RepoRelationship.MONOREPO_PACKAGE,
+ )
+ )
+ return configs
diff --git a/apps/backend/runners/github/onboarding.py b/apps/backend/runners/github/onboarding.py
new file mode 100644
index 00000000..59eb3442
--- /dev/null
+++ b/apps/backend/runners/github/onboarding.py
@@ -0,0 +1,737 @@
+"""
+Onboarding & Progressive Enablement
+====================================
+
+Provides guided setup and progressive enablement for GitHub automation.
+
+Features:
+- Setup wizard for initial configuration
+- Auto-creation of required labels
+- Permission validation during setup
+- Dry run mode (show what WOULD happen)
+- Test mode for first week (comment only)
+- Progressive enablement based on accuracy
+
+Usage:
+ onboarding = OnboardingManager(config, gh_provider)
+
+ # Run setup wizard
+ setup_result = await onboarding.run_setup()
+
+ # Check if in test mode
+ if onboarding.is_test_mode():
+ # Only comment, don't take actions
+
+ # Get onboarding checklist
+ checklist = onboarding.get_checklist()
+
+CLI:
+ python runner.py setup --repo owner/repo
+ python runner.py setup --dry-run
+"""
+
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass, field
+from datetime import datetime, timedelta, timezone
+from enum import Enum
+from pathlib import Path
+from typing import Any
+
+# Import providers
+try:
+ from .providers.protocol import LabelData
+except (ImportError, ValueError, SystemError):
+
+ @dataclass
+ class LabelData:
+ name: str
+ color: str
+ description: str = ""
+
+
+class OnboardingPhase(str, Enum):
+ """Phases of onboarding."""
+
+ NOT_STARTED = "not_started"
+ SETUP_PENDING = "setup_pending"
+ TEST_MODE = "test_mode" # Week 1: Comment only
+ TRIAGE_ENABLED = "triage_enabled" # Week 2: Triage active
+ REVIEW_ENABLED = "review_enabled" # Week 3: PR review active
+ FULL_ENABLED = "full_enabled" # Full automation
+
+
+class EnablementLevel(str, Enum):
+ """Progressive enablement levels."""
+
+ OFF = "off"
+ COMMENT_ONLY = "comment_only" # Test mode
+ TRIAGE_ONLY = "triage_only" # Triage + labeling
+ REVIEW_ONLY = "review_only" # PR reviews
+ FULL = "full" # Everything including auto-fix
+
+
+@dataclass
+class ChecklistItem:
+ """Single item in the onboarding checklist."""
+
+ id: str
+ title: str
+ description: str
+ completed: bool = False
+ required: bool = True
+ completed_at: datetime | None = None
+ error: str | None = None
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "id": self.id,
+ "title": self.title,
+ "description": self.description,
+ "completed": self.completed,
+ "required": self.required,
+ "completed_at": self.completed_at.isoformat()
+ if self.completed_at
+ else None,
+ "error": self.error,
+ }
+
+
+@dataclass
+class SetupResult:
+ """Result of running setup."""
+
+ success: bool
+ phase: OnboardingPhase
+ checklist: list[ChecklistItem]
+ errors: list[str] = field(default_factory=list)
+ warnings: list[str] = field(default_factory=list)
+ dry_run: bool = False
+
+ @property
+ def completion_rate(self) -> float:
+ if not self.checklist:
+ return 0.0
+ completed = sum(1 for item in self.checklist if item.completed)
+ return completed / len(self.checklist)
+
+ @property
+ def required_complete(self) -> bool:
+ return all(item.completed for item in self.checklist if item.required)
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "success": self.success,
+ "phase": self.phase.value,
+ "completion_rate": self.completion_rate,
+ "required_complete": self.required_complete,
+ "checklist": [item.to_dict() for item in self.checklist],
+ "errors": self.errors,
+ "warnings": self.warnings,
+ "dry_run": self.dry_run,
+ }
+
+
+@dataclass
+class OnboardingState:
+ """Persistent onboarding state for a repository."""
+
+ repo: str
+ phase: OnboardingPhase = OnboardingPhase.NOT_STARTED
+ started_at: datetime | None = None
+ completed_items: list[str] = field(default_factory=list)
+ enablement_level: EnablementLevel = EnablementLevel.OFF
+ test_mode_ends_at: datetime | None = None
+ auto_upgrade_enabled: bool = True
+
+ # Accuracy tracking for auto-progression
+ triage_accuracy: float = 0.0
+ triage_actions: int = 0
+ review_accuracy: float = 0.0
+ review_actions: int = 0
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "repo": self.repo,
+ "phase": self.phase.value,
+ "started_at": self.started_at.isoformat() if self.started_at else None,
+ "completed_items": self.completed_items,
+ "enablement_level": self.enablement_level.value,
+ "test_mode_ends_at": self.test_mode_ends_at.isoformat()
+ if self.test_mode_ends_at
+ else None,
+ "auto_upgrade_enabled": self.auto_upgrade_enabled,
+ "triage_accuracy": self.triage_accuracy,
+ "triage_actions": self.triage_actions,
+ "review_accuracy": self.review_accuracy,
+ "review_actions": self.review_actions,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict[str, Any]) -> OnboardingState:
+ started = None
+ if data.get("started_at"):
+ started = datetime.fromisoformat(data["started_at"])
+
+ test_ends = None
+ if data.get("test_mode_ends_at"):
+ test_ends = datetime.fromisoformat(data["test_mode_ends_at"])
+
+ return cls(
+ repo=data["repo"],
+ phase=OnboardingPhase(data.get("phase", "not_started")),
+ started_at=started,
+ completed_items=data.get("completed_items", []),
+ enablement_level=EnablementLevel(data.get("enablement_level", "off")),
+ test_mode_ends_at=test_ends,
+ auto_upgrade_enabled=data.get("auto_upgrade_enabled", True),
+ triage_accuracy=data.get("triage_accuracy", 0.0),
+ triage_actions=data.get("triage_actions", 0),
+ review_accuracy=data.get("review_accuracy", 0.0),
+ review_actions=data.get("review_actions", 0),
+ )
+
+
+# Required labels with their colors and descriptions
+REQUIRED_LABELS = [
+ LabelData(
+ name="auto-fix",
+ color="0E8A16",
+ description="Trigger automatic fix attempt by AI",
+ ),
+ LabelData(
+ name="auto-triage",
+ color="1D76DB",
+ description="Automatically triage and categorize this issue",
+ ),
+ LabelData(
+ name="ai-reviewed",
+ color="5319E7",
+ description="This PR has been reviewed by AI",
+ ),
+ LabelData(
+ name="type:bug",
+ color="D73A4A",
+ description="Something isn't working",
+ ),
+ LabelData(
+ name="type:feature",
+ color="0075CA",
+ description="New feature or request",
+ ),
+ LabelData(
+ name="type:docs",
+ color="0075CA",
+ description="Documentation changes",
+ ),
+ LabelData(
+ name="priority:high",
+ color="B60205",
+ description="High priority issue",
+ ),
+ LabelData(
+ name="priority:medium",
+ color="FBCA04",
+ description="Medium priority issue",
+ ),
+ LabelData(
+ name="priority:low",
+ color="0E8A16",
+ description="Low priority issue",
+ ),
+ LabelData(
+ name="duplicate",
+ color="CFD3D7",
+ description="This issue or PR already exists",
+ ),
+ LabelData(
+ name="spam",
+ color="000000",
+ description="Spam or invalid issue",
+ ),
+]
+
+
+class OnboardingManager:
+ """
+ Manages onboarding and progressive enablement.
+
+ Progressive enablement schedule:
+ - Week 1 (Test Mode): Comment what would be done, no actions
+ - Week 2 (Triage): Enable triage if accuracy > 80%
+ - Week 3 (Review): Enable PR review if triage accuracy > 85%
+ - Week 4+ (Full): Enable auto-fix if review accuracy > 90%
+ """
+
+ # Thresholds for auto-progression
+ TRIAGE_THRESHOLD = 0.80 # 80% accuracy
+ REVIEW_THRESHOLD = 0.85 # 85% accuracy
+ AUTOFIX_THRESHOLD = 0.90 # 90% accuracy
+ MIN_ACTIONS_TO_UPGRADE = 20
+
+ def __init__(
+ self,
+ repo: str,
+ state_dir: Path | None = None,
+ gh_provider: Any = None,
+ ):
+ """
+ Initialize onboarding manager.
+
+ Args:
+ repo: Repository in owner/repo format
+ state_dir: Directory for state files
+ gh_provider: GitHub provider for API calls
+ """
+ self.repo = repo
+ self.state_dir = state_dir or Path(".auto-claude/github")
+ self.gh_provider = gh_provider
+ self._state: OnboardingState | None = None
+
+ @property
+ def state_file(self) -> Path:
+ safe_name = self.repo.replace("/", "_")
+ return self.state_dir / "onboarding" / f"{safe_name}.json"
+
+ def get_state(self) -> OnboardingState:
+ """Get or create onboarding state."""
+ if self._state:
+ return self._state
+
+ if self.state_file.exists():
+ try:
+ with open(self.state_file) as f:
+ data = json.load(f)
+ self._state = OnboardingState.from_dict(data)
+ except (json.JSONDecodeError, KeyError):
+ self._state = OnboardingState(repo=self.repo)
+ else:
+ self._state = OnboardingState(repo=self.repo)
+
+ return self._state
+
+ def save_state(self) -> None:
+ """Save onboarding state."""
+ state = self.get_state()
+ self.state_file.parent.mkdir(parents=True, exist_ok=True)
+ with open(self.state_file, "w") as f:
+ json.dump(state.to_dict(), f, indent=2)
+
+ async def run_setup(
+ self,
+ dry_run: bool = False,
+ skip_labels: bool = False,
+ ) -> SetupResult:
+ """
+ Run the setup wizard.
+
+ Args:
+ dry_run: If True, only report what would be done
+ skip_labels: Skip label creation
+
+ Returns:
+ SetupResult with checklist status
+ """
+ checklist = []
+ errors = []
+ warnings = []
+
+ # 1. Check GitHub authentication
+ auth_item = ChecklistItem(
+ id="auth",
+ title="GitHub Authentication",
+ description="Verify GitHub CLI is authenticated",
+ )
+ try:
+ if self.gh_provider:
+ await self.gh_provider.get_repository_info()
+ auth_item.completed = True
+ auth_item.completed_at = datetime.now(timezone.utc)
+ elif not dry_run:
+ errors.append("No GitHub provider configured")
+ except Exception as e:
+ auth_item.error = str(e)
+ errors.append(f"Authentication failed: {e}")
+ checklist.append(auth_item)
+
+ # 2. Check repository permissions
+ perms_item = ChecklistItem(
+ id="permissions",
+ title="Repository Permissions",
+ description="Verify push access to repository",
+ )
+ try:
+ if self.gh_provider and not dry_run:
+ # Try to get repo info to verify access
+ repo_info = await self.gh_provider.get_repository_info()
+ permissions = repo_info.get("permissions", {})
+ if permissions.get("push"):
+ perms_item.completed = True
+ perms_item.completed_at = datetime.now(timezone.utc)
+ else:
+ perms_item.error = "Missing push permission"
+ warnings.append("Write access recommended for full functionality")
+ elif dry_run:
+ perms_item.completed = True
+ except Exception as e:
+ perms_item.error = str(e)
+ checklist.append(perms_item)
+
+ # 3. Create required labels
+ labels_item = ChecklistItem(
+ id="labels",
+ title="Required Labels",
+ description=f"Create {len(REQUIRED_LABELS)} automation labels",
+ )
+ if skip_labels:
+ labels_item.completed = True
+ labels_item.description = "Skipped (--skip-labels)"
+ elif dry_run:
+ labels_item.completed = True
+ labels_item.description = f"Would create {len(REQUIRED_LABELS)} labels"
+ else:
+ try:
+ if self.gh_provider:
+ created = 0
+ for label in REQUIRED_LABELS:
+ try:
+ await self.gh_provider.create_label(label)
+ created += 1
+ except Exception:
+ pass # Label might already exist
+ labels_item.completed = True
+ labels_item.completed_at = datetime.now(timezone.utc)
+ labels_item.description = f"Created/verified {created} labels"
+ except Exception as e:
+ labels_item.error = str(e)
+ errors.append(f"Label creation failed: {e}")
+ checklist.append(labels_item)
+
+ # 4. Initialize state directory
+ state_item = ChecklistItem(
+ id="state",
+ title="State Directory",
+ description="Create local state directory for automation data",
+ )
+ if dry_run:
+ state_item.completed = True
+ state_item.description = f"Would create {self.state_dir}"
+ else:
+ try:
+ self.state_dir.mkdir(parents=True, exist_ok=True)
+ (self.state_dir / "pr").mkdir(exist_ok=True)
+ (self.state_dir / "issues").mkdir(exist_ok=True)
+ (self.state_dir / "autofix").mkdir(exist_ok=True)
+ (self.state_dir / "audit").mkdir(exist_ok=True)
+ state_item.completed = True
+ state_item.completed_at = datetime.now(timezone.utc)
+ except Exception as e:
+ state_item.error = str(e)
+ errors.append(f"State directory creation failed: {e}")
+ checklist.append(state_item)
+
+ # 5. Validate configuration
+ config_item = ChecklistItem(
+ id="config",
+ title="Configuration",
+ description="Validate automation configuration",
+ required=False,
+ )
+ config_item.completed = True # Placeholder for future validation
+ checklist.append(config_item)
+
+ # Determine success
+ success = all(item.completed for item in checklist if item.required)
+
+ # Update state
+ if success and not dry_run:
+ state = self.get_state()
+ state.phase = OnboardingPhase.TEST_MODE
+ state.started_at = datetime.now(timezone.utc)
+ state.test_mode_ends_at = datetime.now(timezone.utc) + timedelta(days=7)
+ state.enablement_level = EnablementLevel.COMMENT_ONLY
+ state.completed_items = [item.id for item in checklist if item.completed]
+ self.save_state()
+
+ return SetupResult(
+ success=success,
+ phase=OnboardingPhase.TEST_MODE
+ if success
+ else OnboardingPhase.SETUP_PENDING,
+ checklist=checklist,
+ errors=errors,
+ warnings=warnings,
+ dry_run=dry_run,
+ )
+
+ def is_test_mode(self) -> bool:
+ """Check if in test mode (comment only)."""
+ state = self.get_state()
+
+ if state.phase == OnboardingPhase.TEST_MODE:
+ if (
+ state.test_mode_ends_at
+ and datetime.now(timezone.utc) < state.test_mode_ends_at
+ ):
+ return True
+
+ return state.enablement_level == EnablementLevel.COMMENT_ONLY
+
+ def get_enablement_level(self) -> EnablementLevel:
+ """Get current enablement level."""
+ return self.get_state().enablement_level
+
+ def can_perform_action(self, action: str) -> tuple[bool, str]:
+ """
+ Check if an action is allowed under current enablement.
+
+ Args:
+ action: Action to check (triage, review, autofix, label, close)
+
+ Returns:
+ Tuple of (allowed, reason)
+ """
+ level = self.get_enablement_level()
+
+ if level == EnablementLevel.OFF:
+ return False, "Automation is disabled"
+
+ if level == EnablementLevel.COMMENT_ONLY:
+ if action in ("comment",):
+ return True, "Comment-only mode"
+ return False, f"Test mode: would {action} but only commenting"
+
+ if level == EnablementLevel.TRIAGE_ONLY:
+ if action in ("comment", "triage", "label"):
+ return True, "Triage enabled"
+ return False, f"Triage mode: {action} not enabled yet"
+
+ if level == EnablementLevel.REVIEW_ONLY:
+ if action in ("comment", "triage", "label", "review"):
+ return True, "Review enabled"
+ return False, f"Review mode: {action} not enabled yet"
+
+ if level == EnablementLevel.FULL:
+ return True, "Full automation enabled"
+
+ return False, "Unknown enablement level"
+
+ def record_action(
+ self,
+ action_type: str,
+ was_correct: bool,
+ ) -> None:
+ """
+ Record an action outcome for accuracy tracking.
+
+ Args:
+ action_type: Type of action (triage, review)
+ was_correct: Whether the action was correct
+ """
+ state = self.get_state()
+
+ if action_type == "triage":
+ state.triage_actions += 1
+ # Rolling accuracy
+ weight = 1 / state.triage_actions
+ state.triage_accuracy = (
+ state.triage_accuracy * (1 - weight)
+ + (1.0 if was_correct else 0.0) * weight
+ )
+ elif action_type == "review":
+ state.review_actions += 1
+ weight = 1 / state.review_actions
+ state.review_accuracy = (
+ state.review_accuracy * (1 - weight)
+ + (1.0 if was_correct else 0.0) * weight
+ )
+
+ self.save_state()
+
+ def check_progression(self) -> tuple[bool, str | None]:
+ """
+ Check if ready to progress to next enablement level.
+
+ Returns:
+ Tuple of (should_upgrade, message)
+ """
+ state = self.get_state()
+
+ if not state.auto_upgrade_enabled:
+ return False, "Auto-upgrade disabled"
+
+ now = datetime.now(timezone.utc)
+
+ # Test mode -> Triage
+ if state.phase == OnboardingPhase.TEST_MODE:
+ if state.test_mode_ends_at and now >= state.test_mode_ends_at:
+ return True, "Test period complete - ready for triage"
+ days_left = (
+ (state.test_mode_ends_at - now).days if state.test_mode_ends_at else 7
+ )
+ return False, f"Test mode: {days_left} days remaining"
+
+ # Triage -> Review
+ if state.phase == OnboardingPhase.TRIAGE_ENABLED:
+ if (
+ state.triage_actions >= self.MIN_ACTIONS_TO_UPGRADE
+ and state.triage_accuracy >= self.REVIEW_THRESHOLD
+ ):
+ return (
+ True,
+ f"Triage accuracy {state.triage_accuracy:.0%} - ready for reviews",
+ )
+ return (
+ False,
+ f"Triage accuracy: {state.triage_accuracy:.0%} (need {self.REVIEW_THRESHOLD:.0%})",
+ )
+
+ # Review -> Full
+ if state.phase == OnboardingPhase.REVIEW_ENABLED:
+ if (
+ state.review_actions >= self.MIN_ACTIONS_TO_UPGRADE
+ and state.review_accuracy >= self.AUTOFIX_THRESHOLD
+ ):
+ return (
+ True,
+ f"Review accuracy {state.review_accuracy:.0%} - ready for auto-fix",
+ )
+ return (
+ False,
+ f"Review accuracy: {state.review_accuracy:.0%} (need {self.AUTOFIX_THRESHOLD:.0%})",
+ )
+
+ return False, None
+
+ def upgrade_level(self) -> bool:
+ """
+ Upgrade to next enablement level if eligible.
+
+ Returns:
+ True if upgraded
+ """
+ state = self.get_state()
+
+ should_upgrade, _ = self.check_progression()
+ if not should_upgrade:
+ return False
+
+ # Perform upgrade
+ if state.phase == OnboardingPhase.TEST_MODE:
+ state.phase = OnboardingPhase.TRIAGE_ENABLED
+ state.enablement_level = EnablementLevel.TRIAGE_ONLY
+ elif state.phase == OnboardingPhase.TRIAGE_ENABLED:
+ state.phase = OnboardingPhase.REVIEW_ENABLED
+ state.enablement_level = EnablementLevel.REVIEW_ONLY
+ elif state.phase == OnboardingPhase.REVIEW_ENABLED:
+ state.phase = OnboardingPhase.FULL_ENABLED
+ state.enablement_level = EnablementLevel.FULL
+ else:
+ return False
+
+ self.save_state()
+ return True
+
+ def set_enablement_level(self, level: EnablementLevel) -> None:
+ """
+ Manually set enablement level.
+
+ Args:
+ level: Desired enablement level
+ """
+ state = self.get_state()
+ state.enablement_level = level
+ state.auto_upgrade_enabled = False # Disable auto-upgrade on manual override
+
+ # Update phase to match
+ level_to_phase = {
+ EnablementLevel.OFF: OnboardingPhase.NOT_STARTED,
+ EnablementLevel.COMMENT_ONLY: OnboardingPhase.TEST_MODE,
+ EnablementLevel.TRIAGE_ONLY: OnboardingPhase.TRIAGE_ENABLED,
+ EnablementLevel.REVIEW_ONLY: OnboardingPhase.REVIEW_ENABLED,
+ EnablementLevel.FULL: OnboardingPhase.FULL_ENABLED,
+ }
+ state.phase = level_to_phase.get(level, OnboardingPhase.NOT_STARTED)
+
+ self.save_state()
+
+ def get_checklist(self) -> list[ChecklistItem]:
+ """Get the current onboarding checklist."""
+ state = self.get_state()
+
+ items = [
+ ChecklistItem(
+ id="setup",
+ title="Initial Setup",
+ description="Run setup wizard to configure automation",
+ completed=state.phase != OnboardingPhase.NOT_STARTED,
+ ),
+ ChecklistItem(
+ id="test_mode",
+ title="Test Mode (Week 1)",
+ description="AI comments what it would do, no actions taken",
+ completed=state.phase
+ not in {OnboardingPhase.NOT_STARTED, OnboardingPhase.SETUP_PENDING},
+ ),
+ ChecklistItem(
+ id="triage",
+ title="Triage Enabled (Week 2)",
+ description="Automatic issue triage and labeling",
+ completed=state.phase
+ in {
+ OnboardingPhase.TRIAGE_ENABLED,
+ OnboardingPhase.REVIEW_ENABLED,
+ OnboardingPhase.FULL_ENABLED,
+ },
+ ),
+ ChecklistItem(
+ id="review",
+ title="PR Review Enabled (Week 3)",
+ description="Automatic PR code reviews",
+ completed=state.phase
+ in {
+ OnboardingPhase.REVIEW_ENABLED,
+ OnboardingPhase.FULL_ENABLED,
+ },
+ ),
+ ChecklistItem(
+ id="autofix",
+ title="Auto-Fix Enabled (Week 4+)",
+ description="Full autonomous issue fixing",
+ completed=state.phase == OnboardingPhase.FULL_ENABLED,
+ required=False,
+ ),
+ ]
+
+ return items
+
+ def get_status_summary(self) -> dict[str, Any]:
+ """Get summary of onboarding status."""
+ state = self.get_state()
+ checklist = self.get_checklist()
+
+ should_upgrade, upgrade_message = self.check_progression()
+
+ return {
+ "repo": self.repo,
+ "phase": state.phase.value,
+ "enablement_level": state.enablement_level.value,
+ "started_at": state.started_at.isoformat() if state.started_at else None,
+ "test_mode_ends_at": state.test_mode_ends_at.isoformat()
+ if state.test_mode_ends_at
+ else None,
+ "is_test_mode": self.is_test_mode(),
+ "checklist": [item.to_dict() for item in checklist],
+ "accuracy": {
+ "triage": state.triage_accuracy,
+ "triage_actions": state.triage_actions,
+ "review": state.review_accuracy,
+ "review_actions": state.review_actions,
+ },
+ "progression": {
+ "ready_to_upgrade": should_upgrade,
+ "message": upgrade_message,
+ "auto_upgrade_enabled": state.auto_upgrade_enabled,
+ },
+ }
diff --git a/apps/backend/runners/github/orchestrator.py b/apps/backend/runners/github/orchestrator.py
new file mode 100644
index 00000000..3ec71724
--- /dev/null
+++ b/apps/backend/runners/github/orchestrator.py
@@ -0,0 +1,1086 @@
+"""
+GitHub Automation Orchestrator
+==============================
+
+Main coordinator for all GitHub automation workflows:
+- PR Review: AI-powered code review
+- Issue Triage: Classification and labeling
+- Issue Auto-Fix: Automatic spec creation and execution
+
+This is a STANDALONE system - does not modify existing task execution pipeline.
+
+REFACTORED: Service layer architecture - orchestrator delegates to specialized services.
+"""
+
+from __future__ import annotations
+
+from collections.abc import Callable
+from dataclasses import dataclass
+from pathlib import Path
+
+try:
+ # When imported as part of package
+ from .bot_detection import BotDetector
+ from .context_gatherer import PRContext, PRContextGatherer
+ from .gh_client import GHClient
+ from .models import (
+ AICommentTriage,
+ AICommentVerdict,
+ AutoFixState,
+ GitHubRunnerConfig,
+ MergeVerdict,
+ PRReviewFinding,
+ PRReviewResult,
+ ReviewCategory,
+ ReviewSeverity,
+ StructuralIssue,
+ TriageResult,
+ )
+ from .permissions import GitHubPermissionChecker
+ from .rate_limiter import RateLimiter
+ from .services import (
+ AutoFixProcessor,
+ BatchProcessor,
+ PRReviewEngine,
+ TriageEngine,
+ )
+except (ImportError, ValueError, SystemError):
+ # When imported directly (runner.py adds github dir to path)
+ from bot_detection import BotDetector
+ from context_gatherer import PRContext, PRContextGatherer
+ from gh_client import GHClient
+ from models import (
+ AICommentTriage,
+ AICommentVerdict,
+ AutoFixState,
+ GitHubRunnerConfig,
+ MergeVerdict,
+ PRReviewFinding,
+ PRReviewResult,
+ ReviewCategory,
+ ReviewSeverity,
+ StructuralIssue,
+ TriageResult,
+ )
+ from permissions import GitHubPermissionChecker
+ from rate_limiter import RateLimiter
+ from services import (
+ AutoFixProcessor,
+ BatchProcessor,
+ PRReviewEngine,
+ TriageEngine,
+ )
+
+
+@dataclass
+class ProgressCallback:
+ """Callback for progress updates."""
+
+ phase: str
+ progress: int # 0-100
+ message: str
+ issue_number: int | None = None
+ pr_number: int | None = None
+
+
+class GitHubOrchestrator:
+ """
+ Orchestrates all GitHub automation workflows.
+
+ This is a thin coordinator that delegates to specialized service classes:
+ - PRReviewEngine: Multi-pass code review
+ - TriageEngine: Issue classification
+ - AutoFixProcessor: Automatic issue fixing
+ - BatchProcessor: Batch issue processing
+
+ Usage:
+ orchestrator = GitHubOrchestrator(
+ project_dir=Path("/path/to/project"),
+ config=config,
+ )
+
+ # Review a PR
+ result = await orchestrator.review_pr(pr_number=123)
+
+ # Triage issues
+ results = await orchestrator.triage_issues(issue_numbers=[1, 2, 3])
+
+ # Auto-fix an issue
+ state = await orchestrator.auto_fix_issue(issue_number=456)
+ """
+
+ def __init__(
+ self,
+ project_dir: Path,
+ config: GitHubRunnerConfig,
+ progress_callback: Callable[[ProgressCallback], None] | None = None,
+ ):
+ self.project_dir = Path(project_dir)
+ self.config = config
+ self.progress_callback = progress_callback
+
+ # GitHub directory for storing state
+ self.github_dir = self.project_dir / ".auto-claude" / "github"
+ self.github_dir.mkdir(parents=True, exist_ok=True)
+
+ # Initialize GH client with timeout protection
+ self.gh_client = GHClient(
+ project_dir=self.project_dir,
+ default_timeout=30.0,
+ max_retries=3,
+ enable_rate_limiting=True,
+ )
+
+ # Initialize bot detector for preventing infinite loops
+ self.bot_detector = BotDetector(
+ state_dir=self.github_dir,
+ bot_token=config.bot_token,
+ review_own_prs=config.review_own_prs,
+ )
+
+ # Initialize permission checker for auto-fix authorization
+ self.permission_checker = GitHubPermissionChecker(
+ gh_client=self.gh_client,
+ repo=config.repo,
+ allowed_roles=config.auto_fix_allowed_roles,
+ allow_external_contributors=config.allow_external_contributors,
+ )
+
+ # Initialize rate limiter singleton
+ self.rate_limiter = RateLimiter.get_instance()
+
+ # Initialize service layer
+ self.pr_review_engine = PRReviewEngine(
+ project_dir=self.project_dir,
+ github_dir=self.github_dir,
+ config=self.config,
+ progress_callback=self.progress_callback,
+ )
+
+ self.triage_engine = TriageEngine(
+ project_dir=self.project_dir,
+ github_dir=self.github_dir,
+ config=self.config,
+ progress_callback=self.progress_callback,
+ )
+
+ self.autofix_processor = AutoFixProcessor(
+ github_dir=self.github_dir,
+ config=self.config,
+ permission_checker=self.permission_checker,
+ progress_callback=self.progress_callback,
+ )
+
+ self.batch_processor = BatchProcessor(
+ project_dir=self.project_dir,
+ github_dir=self.github_dir,
+ config=self.config,
+ progress_callback=self.progress_callback,
+ )
+
+ def _report_progress(
+ self,
+ phase: str,
+ progress: int,
+ message: str,
+ issue_number: int | None = None,
+ pr_number: int | None = None,
+ ) -> None:
+ """Report progress to callback if set."""
+ if self.progress_callback:
+ self.progress_callback(
+ ProgressCallback(
+ phase=phase,
+ progress=progress,
+ message=message,
+ issue_number=issue_number,
+ pr_number=pr_number,
+ )
+ )
+
+ # =========================================================================
+ # GitHub API Helpers
+ # =========================================================================
+
+ async def _fetch_pr_data(self, pr_number: int) -> dict:
+ """Fetch PR data from GitHub API via gh CLI."""
+ return await self.gh_client.pr_get(pr_number)
+
+ async def _fetch_pr_diff(self, pr_number: int) -> str:
+ """Fetch PR diff from GitHub."""
+ return await self.gh_client.pr_diff(pr_number)
+
+ async def _fetch_issue_data(self, issue_number: int) -> dict:
+ """Fetch issue data from GitHub API via gh CLI."""
+ return await self.gh_client.issue_get(issue_number)
+
+ async def _fetch_open_issues(self, limit: int = 200) -> list[dict]:
+ """Fetch all open issues from the repository (up to 200)."""
+ return await self.gh_client.issue_list(state="open", limit=limit)
+
+ async def _post_pr_review(
+ self,
+ pr_number: int,
+ body: str,
+ event: str = "COMMENT",
+ ) -> int:
+ """Post a review to a PR."""
+ return await self.gh_client.pr_review(
+ pr_number=pr_number,
+ body=body,
+ event=event.lower(),
+ )
+
+ async def _post_issue_comment(self, issue_number: int, body: str) -> None:
+ """Post a comment to an issue."""
+ await self.gh_client.issue_comment(issue_number, body)
+
+ async def _add_issue_labels(self, issue_number: int, labels: list[str]) -> None:
+ """Add labels to an issue."""
+ await self.gh_client.issue_add_labels(issue_number, labels)
+
+ async def _remove_issue_labels(self, issue_number: int, labels: list[str]) -> None:
+ """Remove labels from an issue."""
+ await self.gh_client.issue_remove_labels(issue_number, labels)
+
+ async def _post_ai_triage_replies(
+ self, pr_number: int, triages: list[AICommentTriage]
+ ) -> None:
+ """Post replies to AI tool comments based on triage results."""
+ for triage in triages:
+ if not triage.response_comment:
+ continue
+
+ # Skip trivial verdicts
+ if triage.verdict == AICommentVerdict.TRIVIAL:
+ continue
+
+ try:
+ # Post as inline comment reply
+ await self.gh_client.pr_comment_reply(
+ pr_number=pr_number,
+ comment_id=triage.comment_id,
+ body=triage.response_comment,
+ )
+ print(
+ f"[AI TRIAGE] Posted reply to {triage.tool_name} comment {triage.comment_id}",
+ flush=True,
+ )
+ except Exception as e:
+ print(
+ f"[AI TRIAGE] Failed to post reply to comment {triage.comment_id}: {e}",
+ flush=True,
+ )
+
+ # =========================================================================
+ # PR REVIEW WORKFLOW
+ # =========================================================================
+
+ async def review_pr(self, pr_number: int) -> PRReviewResult:
+ """
+ Perform AI-powered review of a pull request.
+
+ Args:
+ pr_number: The PR number to review
+
+ Returns:
+ PRReviewResult with findings and overall assessment
+ """
+ print(
+ f"[DEBUG orchestrator] review_pr() called for PR #{pr_number}", flush=True
+ )
+
+ self._report_progress(
+ "gathering_context",
+ 10,
+ f"Gathering context for PR #{pr_number}...",
+ pr_number=pr_number,
+ )
+
+ try:
+ # Gather PR context
+ print("[DEBUG orchestrator] Creating context gatherer...", flush=True)
+ gatherer = PRContextGatherer(self.project_dir, pr_number)
+
+ print("[DEBUG orchestrator] Gathering PR context...", flush=True)
+ pr_context = await gatherer.gather()
+ print(
+ f"[DEBUG orchestrator] Context gathered: {pr_context.title} "
+ f"({len(pr_context.changed_files)} files, {len(pr_context.related_files)} related)",
+ flush=True,
+ )
+
+ # Bot detection check
+ pr_data = {"author": {"login": pr_context.author}}
+ should_skip, skip_reason = self.bot_detector.should_skip_pr_review(
+ pr_number=pr_number,
+ pr_data=pr_data,
+ commits=pr_context.commits,
+ )
+
+ if should_skip:
+ print(
+ f"[BOT DETECTION] Skipping PR #{pr_number}: {skip_reason}",
+ flush=True,
+ )
+ result = PRReviewResult(
+ pr_number=pr_number,
+ repo=self.config.repo,
+ success=True,
+ findings=[],
+ summary=f"Skipped review: {skip_reason}",
+ overall_status="comment",
+ )
+ await result.save(self.github_dir)
+ return result
+
+ self._report_progress(
+ "analyzing", 30, "Running multi-pass review...", pr_number=pr_number
+ )
+
+ # Delegate to PR Review Engine
+ print("[DEBUG orchestrator] Running multi-pass review...", flush=True)
+ (
+ findings,
+ structural_issues,
+ ai_triages,
+ quick_scan,
+ ) = await self.pr_review_engine.run_multi_pass_review(pr_context)
+ print(
+ f"[DEBUG orchestrator] Multi-pass review complete: "
+ f"{len(findings)} findings, {len(structural_issues)} structural, {len(ai_triages)} AI triages",
+ flush=True,
+ )
+
+ self._report_progress(
+ "generating",
+ 70,
+ "Generating verdict and summary...",
+ pr_number=pr_number,
+ )
+
+ # Generate verdict
+ verdict, verdict_reasoning, blockers = self._generate_verdict(
+ findings, structural_issues, ai_triages
+ )
+ print(
+ f"[DEBUG orchestrator] Verdict: {verdict.value} - {verdict_reasoning}",
+ flush=True,
+ )
+
+ # Calculate risk assessment
+ risk_assessment = self._calculate_risk_assessment(
+ pr_context, findings, structural_issues
+ )
+
+ # Map verdict to overall_status for backward compatibility
+ if verdict == MergeVerdict.BLOCKED:
+ overall_status = "request_changes"
+ elif verdict == MergeVerdict.NEEDS_REVISION:
+ overall_status = "request_changes"
+ elif verdict == MergeVerdict.MERGE_WITH_CHANGES:
+ overall_status = "comment"
+ else:
+ overall_status = "approve"
+
+ # Generate summary
+ summary = self._generate_enhanced_summary(
+ verdict=verdict,
+ verdict_reasoning=verdict_reasoning,
+ blockers=blockers,
+ findings=findings,
+ structural_issues=structural_issues,
+ ai_triages=ai_triages,
+ risk_assessment=risk_assessment,
+ )
+
+ # Get HEAD SHA for follow-up review tracking
+ head_sha = self.bot_detector.get_last_commit_sha(pr_context.commits)
+
+ # Create result
+ result = PRReviewResult(
+ pr_number=pr_number,
+ repo=self.config.repo,
+ success=True,
+ findings=findings,
+ summary=summary,
+ overall_status=overall_status,
+ verdict=verdict,
+ verdict_reasoning=verdict_reasoning,
+ blockers=blockers,
+ risk_assessment=risk_assessment,
+ structural_issues=structural_issues,
+ ai_comment_triages=ai_triages,
+ quick_scan_summary=quick_scan,
+ # Track the commit SHA for follow-up reviews
+ reviewed_commit_sha=head_sha,
+ )
+
+ # Post review if configured
+ if self.config.auto_post_reviews:
+ self._report_progress(
+ "posting", 90, "Posting review to GitHub...", pr_number=pr_number
+ )
+ review_id = await self._post_pr_review(
+ pr_number=pr_number,
+ body=self._format_review_body(result),
+ event=overall_status.upper(),
+ )
+ result.review_id = review_id
+
+ # Post AI triage replies
+ if ai_triages:
+ self._report_progress(
+ "posting",
+ 95,
+ "Posting AI triage replies...",
+ pr_number=pr_number,
+ )
+ await self._post_ai_triage_replies(pr_number, ai_triages)
+
+ # Save result
+ await result.save(self.github_dir)
+
+ # Mark as reviewed (head_sha already fetched above)
+ if head_sha:
+ self.bot_detector.mark_reviewed(pr_number, head_sha)
+
+ self._report_progress(
+ "complete", 100, "Review complete!", pr_number=pr_number
+ )
+ return result
+
+ except Exception as e:
+ import traceback
+
+ # Log full exception details for debugging
+ error_details = f"{type(e).__name__}: {e}"
+ full_traceback = traceback.format_exc()
+ print(
+ f"[ERROR orchestrator] PR review failed for #{pr_number}: {error_details}",
+ flush=True,
+ )
+ print(f"[ERROR orchestrator] Full traceback:\n{full_traceback}", flush=True)
+
+ result = PRReviewResult(
+ pr_number=pr_number,
+ repo=self.config.repo,
+ success=False,
+ error=f"{error_details}\n\nTraceback:\n{full_traceback}",
+ )
+ await result.save(self.github_dir)
+ return result
+
+ async def followup_review_pr(self, pr_number: int) -> PRReviewResult:
+ """
+ Perform a focused follow-up review of a PR.
+
+ Only reviews:
+ - Changes since last review (new commits)
+ - Whether previous findings are resolved
+ - New comments from contributors and AI bots
+
+ Args:
+ pr_number: The PR number to review
+
+ Returns:
+ PRReviewResult with follow-up analysis
+
+ Raises:
+ ValueError: If no previous review exists for this PR
+ """
+ print(
+ f"[DEBUG orchestrator] followup_review_pr() called for PR #{pr_number}",
+ flush=True,
+ )
+
+ # Load previous review
+ previous_review = PRReviewResult.load(self.github_dir, pr_number)
+
+ if not previous_review:
+ raise ValueError(
+ f"No previous review found for PR #{pr_number}. Run initial review first."
+ )
+
+ if not previous_review.reviewed_commit_sha:
+ raise ValueError(
+ f"Previous review for PR #{pr_number} doesn't have commit SHA. "
+ "Re-run initial review with the updated system."
+ )
+
+ self._report_progress(
+ "gathering_context",
+ 10,
+ f"Gathering follow-up context for PR #{pr_number}...",
+ pr_number=pr_number,
+ )
+
+ try:
+ # Import here to avoid circular imports at module level
+ try:
+ from .context_gatherer import FollowupContextGatherer
+ from .services.followup_reviewer import FollowupReviewer
+ except (ImportError, ValueError, SystemError):
+ from context_gatherer import FollowupContextGatherer
+ from services.followup_reviewer import FollowupReviewer
+
+ # Gather follow-up context
+ gatherer = FollowupContextGatherer(
+ self.project_dir,
+ pr_number,
+ previous_review,
+ )
+ followup_context = await gatherer.gather()
+
+ # Check if there are new commits
+ if not followup_context.commits_since_review:
+ print(
+ f"[Followup] No new commits since last review at {previous_review.reviewed_commit_sha[:8]}",
+ flush=True,
+ )
+ # Return a result indicating no changes
+ result = PRReviewResult(
+ pr_number=pr_number,
+ repo=self.config.repo,
+ success=True,
+ findings=previous_review.findings,
+ summary="No new commits since last review. Previous findings still apply.",
+ overall_status=previous_review.overall_status,
+ verdict=previous_review.verdict,
+ verdict_reasoning="No changes since last review.",
+ reviewed_commit_sha=followup_context.current_commit_sha
+ or previous_review.reviewed_commit_sha,
+ is_followup_review=True,
+ unresolved_findings=[f.id for f in previous_review.findings],
+ )
+ await result.save(self.github_dir)
+ return result
+
+ self._report_progress(
+ "analyzing",
+ 30,
+ f"Analyzing {len(followup_context.commits_since_review)} new commits...",
+ pr_number=pr_number,
+ )
+
+ # Run follow-up review
+ reviewer = FollowupReviewer(
+ project_dir=self.project_dir,
+ github_dir=self.github_dir,
+ config=self.config,
+ progress_callback=lambda p: self._report_progress(
+ p.get("phase", "analyzing"),
+ p.get("progress", 50),
+ p.get("message", "Reviewing..."),
+ pr_number=pr_number,
+ ),
+ )
+
+ result = await reviewer.review_followup(followup_context)
+
+ # Save result
+ await result.save(self.github_dir)
+
+ # Mark as reviewed with new commit SHA
+ if result.reviewed_commit_sha:
+ self.bot_detector.mark_reviewed(pr_number, result.reviewed_commit_sha)
+
+ self._report_progress(
+ "complete", 100, "Follow-up review complete!", pr_number=pr_number
+ )
+
+ return result
+
+ except Exception as e:
+ result = PRReviewResult(
+ pr_number=pr_number,
+ repo=self.config.repo,
+ success=False,
+ error=str(e),
+ is_followup_review=True,
+ )
+ await result.save(self.github_dir)
+ return result
+
+ def _generate_verdict(
+ self,
+ findings: list[PRReviewFinding],
+ structural_issues: list[StructuralIssue],
+ ai_triages: list[AICommentTriage],
+ ) -> tuple[MergeVerdict, str, list[str]]:
+ """
+ Generate merge verdict based on all findings.
+
+ NEW: Strengthened to block on verification failures and redundancy issues.
+ """
+ blockers = []
+
+ # Count by severity
+ critical = [f for f in findings if f.severity == ReviewSeverity.CRITICAL]
+ high = [f for f in findings if f.severity == ReviewSeverity.HIGH]
+
+ # NEW: Verification failures are ALWAYS blockers (even if not critical severity)
+ verification_failures = [
+ f for f in findings if f.category == ReviewCategory.VERIFICATION_FAILED
+ ]
+
+ # NEW: High severity redundancy issues are blockers
+ redundancy_issues = [
+ f
+ for f in findings
+ if f.category == ReviewCategory.REDUNDANCY
+ and f.severity in (ReviewSeverity.CRITICAL, ReviewSeverity.HIGH)
+ ]
+
+ # Security findings are always blockers
+ security_critical = [
+ f for f in critical if f.category == ReviewCategory.SECURITY
+ ]
+
+ # Structural blockers
+ structural_blockers = [
+ s
+ for s in structural_issues
+ if s.severity in (ReviewSeverity.CRITICAL, ReviewSeverity.HIGH)
+ ]
+
+ # AI comments marked critical
+ ai_critical = [t for t in ai_triages if t.verdict == AICommentVerdict.CRITICAL]
+
+ # Build blockers list with NEW categories first
+ # NEW: Verification failures block merging
+ for f in verification_failures:
+ note = f" - {f.verification_note}" if f.verification_note else ""
+ blockers.append(f"Verification Failed: {f.title} ({f.file}:{f.line}){note}")
+
+ # NEW: Redundancy issues block merging
+ for f in redundancy_issues:
+ redundant_ref = (
+ f" (duplicates {f.redundant_with})" if f.redundant_with else ""
+ )
+ blockers.append(f"Redundancy: {f.title} ({f.file}:{f.line}){redundant_ref}")
+
+ # Existing blocker categories
+ for f in security_critical:
+ blockers.append(f"Security: {f.title} ({f.file}:{f.line})")
+ for f in critical:
+ if (
+ f not in security_critical
+ and f not in verification_failures
+ and f not in redundancy_issues
+ ):
+ blockers.append(f"Critical: {f.title} ({f.file}:{f.line})")
+ for s in structural_blockers:
+ blockers.append(f"Structure: {s.title}")
+ for t in ai_critical:
+ summary = (
+ t.original_comment[:50] + "..."
+ if len(t.original_comment) > 50
+ else t.original_comment
+ )
+ blockers.append(f"{t.tool_name}: {summary}")
+
+ # Determine verdict with NEW verification and redundancy checks
+ if blockers:
+ # NEW: Prioritize verification failures
+ if verification_failures:
+ verdict = MergeVerdict.BLOCKED
+ reasoning = (
+ f"Blocked: Cannot verify {len(verification_failures)} claim(s) in PR. "
+ "Evidence required before merge."
+ )
+ elif security_critical:
+ verdict = MergeVerdict.BLOCKED
+ reasoning = (
+ f"Blocked by {len(security_critical)} security vulnerabilities"
+ )
+ elif redundancy_issues:
+ verdict = MergeVerdict.BLOCKED
+ reasoning = (
+ f"Blocked: {len(redundancy_issues)} redundant implementation(s) detected. "
+ "Remove duplicates before merge."
+ )
+ elif len(critical) > 0:
+ verdict = MergeVerdict.BLOCKED
+ reasoning = f"Blocked by {len(critical)} critical issues"
+ else:
+ verdict = MergeVerdict.NEEDS_REVISION
+ reasoning = f"{len(blockers)} issues must be addressed"
+ elif high:
+ verdict = MergeVerdict.MERGE_WITH_CHANGES
+ reasoning = f"{len(high)} high-priority issues to address"
+ else:
+ verdict = MergeVerdict.READY_TO_MERGE
+ reasoning = "No blocking issues found"
+
+ return verdict, reasoning, blockers
+
+ def _calculate_risk_assessment(
+ self,
+ context: PRContext,
+ findings: list[PRReviewFinding],
+ structural_issues: list[StructuralIssue],
+ ) -> dict:
+ """Calculate risk assessment for the PR."""
+ total_changes = context.total_additions + context.total_deletions
+
+ # Complexity
+ if total_changes > 500:
+ complexity = "high"
+ elif total_changes > 200:
+ complexity = "medium"
+ else:
+ complexity = "low"
+
+ # Security impact
+ security_findings = [
+ f for f in findings if f.category == ReviewCategory.SECURITY
+ ]
+ if any(f.severity == ReviewSeverity.CRITICAL for f in security_findings):
+ security_impact = "critical"
+ elif any(f.severity == ReviewSeverity.HIGH for f in security_findings):
+ security_impact = "medium"
+ elif security_findings:
+ security_impact = "low"
+ else:
+ security_impact = "none"
+
+ # Scope coherence
+ scope_issues = [
+ s
+ for s in structural_issues
+ if s.issue_type in ("feature_creep", "scope_creep")
+ ]
+ if any(
+ s.severity in (ReviewSeverity.CRITICAL, ReviewSeverity.HIGH)
+ for s in scope_issues
+ ):
+ scope_coherence = "poor"
+ elif scope_issues:
+ scope_coherence = "mixed"
+ else:
+ scope_coherence = "good"
+
+ return {
+ "complexity": complexity,
+ "security_impact": security_impact,
+ "scope_coherence": scope_coherence,
+ }
+
+ def _generate_enhanced_summary(
+ self,
+ verdict: MergeVerdict,
+ verdict_reasoning: str,
+ blockers: list[str],
+ findings: list[PRReviewFinding],
+ structural_issues: list[StructuralIssue],
+ ai_triages: list[AICommentTriage],
+ risk_assessment: dict,
+ ) -> str:
+ """Generate enhanced summary with verdict, risk, and actionable next steps."""
+ verdict_emoji = {
+ MergeVerdict.READY_TO_MERGE: "✅",
+ MergeVerdict.MERGE_WITH_CHANGES: "🟡",
+ MergeVerdict.NEEDS_REVISION: "🟠",
+ MergeVerdict.BLOCKED: "🔴",
+ }
+
+ lines = [
+ f"### Merge Verdict: {verdict_emoji.get(verdict, '⚪')} {verdict.value.upper().replace('_', ' ')}",
+ verdict_reasoning,
+ "",
+ "### Risk Assessment",
+ "| Factor | Level | Notes |",
+ "|--------|-------|-------|",
+ f"| Complexity | {risk_assessment['complexity'].capitalize()} | Based on lines changed |",
+ f"| Security Impact | {risk_assessment['security_impact'].capitalize()} | Based on security findings |",
+ f"| Scope Coherence | {risk_assessment['scope_coherence'].capitalize()} | Based on structural review |",
+ "",
+ ]
+
+ # Blockers
+ if blockers:
+ lines.append("### 🚨 Blocking Issues (Must Fix)")
+ for blocker in blockers:
+ lines.append(f"- {blocker}")
+ lines.append("")
+
+ # Findings summary
+ if findings:
+ by_severity = {}
+ for f in findings:
+ severity = f.severity.value
+ if severity not in by_severity:
+ by_severity[severity] = []
+ by_severity[severity].append(f)
+
+ lines.append("### Findings Summary")
+ for severity in ["critical", "high", "medium", "low"]:
+ if severity in by_severity:
+ count = len(by_severity[severity])
+ lines.append(f"- **{severity.capitalize()}**: {count} issue(s)")
+ lines.append("")
+
+ # Structural issues
+ if structural_issues:
+ lines.append("### 🏗️ Structural Issues")
+ for issue in structural_issues[:5]:
+ lines.append(f"- **{issue.title}**: {issue.description}")
+ if len(structural_issues) > 5:
+ lines.append(f"- ... and {len(structural_issues) - 5} more")
+ lines.append("")
+
+ # AI triages summary
+ if ai_triages:
+ critical_ai = [
+ t for t in ai_triages if t.verdict == AICommentVerdict.CRITICAL
+ ]
+ important_ai = [
+ t for t in ai_triages if t.verdict == AICommentVerdict.IMPORTANT
+ ]
+ if critical_ai or important_ai:
+ lines.append("### 🤖 AI Tool Comments Review")
+ if critical_ai:
+ lines.append(f"- **Critical**: {len(critical_ai)} validated issues")
+ if important_ai:
+ lines.append(
+ f"- **Important**: {len(important_ai)} recommended fixes"
+ )
+ lines.append("")
+
+ lines.append("---")
+ lines.append("_Generated by Auto Claude PR Review_")
+
+ return "\n".join(lines)
+
+ def _format_review_body(self, result: PRReviewResult) -> str:
+ """Format the review body for posting to GitHub."""
+ return result.summary
+
+ # =========================================================================
+ # ISSUE TRIAGE WORKFLOW
+ # =========================================================================
+
+ async def triage_issues(
+ self,
+ issue_numbers: list[int] | None = None,
+ apply_labels: bool = False,
+ ) -> list[TriageResult]:
+ """
+ Triage issues to detect duplicates, spam, and feature creep.
+
+ Args:
+ issue_numbers: Specific issues to triage, or None for all open issues
+ apply_labels: Whether to apply suggested labels to GitHub
+
+ Returns:
+ List of TriageResult for each issue
+ """
+ self._report_progress("fetching", 10, "Fetching issues...")
+
+ # Fetch issues
+ if issue_numbers:
+ issues = []
+ for num in issue_numbers:
+ issues.append(await self._fetch_issue_data(num))
+ else:
+ issues = await self._fetch_open_issues()
+
+ if not issues:
+ return []
+
+ results = []
+ total = len(issues)
+
+ for i, issue in enumerate(issues):
+ progress = 20 + int(60 * (i / total))
+ self._report_progress(
+ "analyzing",
+ progress,
+ f"Analyzing issue #{issue['number']}...",
+ issue_number=issue["number"],
+ )
+
+ # Delegate to triage engine
+ result = await self.triage_engine.triage_single_issue(issue, issues)
+ results.append(result)
+
+ # Apply labels if requested
+ if apply_labels and (result.labels_to_add or result.labels_to_remove):
+ try:
+ await self._add_issue_labels(issue["number"], result.labels_to_add)
+ await self._remove_issue_labels(
+ issue["number"], result.labels_to_remove
+ )
+ except Exception as e:
+ print(f"Failed to apply labels to #{issue['number']}: {e}")
+
+ # Save result
+ await result.save(self.github_dir)
+
+ self._report_progress("complete", 100, f"Triaged {len(results)} issues")
+ return results
+
+ # =========================================================================
+ # AUTO-FIX WORKFLOW
+ # =========================================================================
+
+ async def auto_fix_issue(
+ self,
+ issue_number: int,
+ trigger_label: str | None = None,
+ ) -> AutoFixState:
+ """
+ Automatically fix an issue by creating a spec and running the build pipeline.
+
+ Args:
+ issue_number: The issue number to fix
+ trigger_label: Label that triggered this auto-fix (for permission checks)
+
+ Returns:
+ AutoFixState tracking the fix progress
+
+ Raises:
+ PermissionError: If the user who added the trigger label isn't authorized
+ """
+ # Fetch issue data
+ issue = await self._fetch_issue_data(issue_number)
+
+ # Delegate to autofix processor
+ return await self.autofix_processor.process_issue(
+ issue_number=issue_number,
+ issue=issue,
+ trigger_label=trigger_label,
+ )
+
+ async def get_auto_fix_queue(self) -> list[AutoFixState]:
+ """Get all issues in the auto-fix queue."""
+ return await self.autofix_processor.get_queue()
+
+ async def check_auto_fix_labels(
+ self, verify_permissions: bool = True
+ ) -> list[dict]:
+ """
+ Check for issues with auto-fix labels and return their details.
+
+ Args:
+ verify_permissions: Whether to verify who added the trigger label
+
+ Returns:
+ List of dicts with issue_number, trigger_label, and authorized status
+ """
+ issues = await self._fetch_open_issues()
+ return await self.autofix_processor.check_labeled_issues(
+ all_issues=issues,
+ verify_permissions=verify_permissions,
+ )
+
+ async def check_new_issues(self) -> list[dict]:
+ """
+ Check for NEW issues that aren't already in the auto-fix queue.
+
+ Returns:
+ List of dicts with just the issue number: [{"number": 123}, ...]
+ """
+ # Get all open issues
+ issues = await self._fetch_open_issues()
+
+ # Get current queue to filter out issues already being processed
+ queue = await self.get_auto_fix_queue()
+ queued_issue_numbers = {state.issue_number for state in queue}
+
+ # Return just the issue numbers (not full issue objects to avoid huge JSON)
+ new_issues = [
+ {"number": issue["number"]}
+ for issue in issues
+ if issue["number"] not in queued_issue_numbers
+ ]
+
+ return new_issues
+
+ # =========================================================================
+ # BATCH AUTO-FIX WORKFLOW
+ # =========================================================================
+
+ async def batch_and_fix_issues(
+ self,
+ issue_numbers: list[int] | None = None,
+ ) -> list:
+ """
+ Batch similar issues and create combined specs for each batch.
+
+ Args:
+ issue_numbers: Specific issues to batch, or None for all open issues
+
+ Returns:
+ List of IssueBatch objects that were created
+ """
+ # Fetch issues
+ if issue_numbers:
+ issues = []
+ for num in issue_numbers:
+ issue = await self._fetch_issue_data(num)
+ issues.append(issue)
+ else:
+ issues = await self._fetch_open_issues()
+
+ # Delegate to batch processor
+ return await self.batch_processor.batch_and_fix_issues(
+ issues=issues,
+ fetch_issue_callback=self._fetch_issue_data,
+ )
+
+ async def analyze_issues_preview(
+ self,
+ issue_numbers: list[int] | None = None,
+ max_issues: int = 200,
+ ) -> dict:
+ """
+ Analyze issues and return a PREVIEW of proposed batches without executing.
+
+ Args:
+ issue_numbers: Specific issues to analyze, or None for all open issues
+ max_issues: Maximum number of issues to analyze (default 200)
+
+ Returns:
+ Dict with proposed batches and statistics for user review
+ """
+ # Fetch issues
+ if issue_numbers:
+ issues = []
+ for num in issue_numbers[:max_issues]:
+ issue = await self._fetch_issue_data(num)
+ issues.append(issue)
+ else:
+ issues = await self._fetch_open_issues(limit=max_issues)
+
+ # Delegate to batch processor
+ return await self.batch_processor.analyze_issues_preview(
+ issues=issues,
+ max_issues=max_issues,
+ )
+
+ async def approve_and_execute_batches(
+ self,
+ approved_batches: list[dict],
+ ) -> list:
+ """
+ Execute approved batches after user review.
+
+ Args:
+ approved_batches: List of batch dicts from analyze_issues_preview
+
+ Returns:
+ List of created IssueBatch objects
+ """
+ return await self.batch_processor.approve_and_execute_batches(
+ approved_batches=approved_batches,
+ )
+
+ async def get_batch_status(self) -> dict:
+ """Get status of all batches."""
+ return await self.batch_processor.get_batch_status()
+
+ async def process_pending_batches(self) -> int:
+ """Process all pending batches."""
+ return await self.batch_processor.process_pending_batches()
diff --git a/apps/backend/runners/github/output_validator.py b/apps/backend/runners/github/output_validator.py
new file mode 100644
index 00000000..4f29e508
--- /dev/null
+++ b/apps/backend/runners/github/output_validator.py
@@ -0,0 +1,518 @@
+"""
+Output Validation Module for PR Review System
+=============================================
+
+Validates and improves the quality of AI-generated PR review findings.
+Filters out false positives, verifies line numbers, and scores actionability.
+"""
+
+from __future__ import annotations
+
+import re
+from pathlib import Path
+from typing import Any
+
+try:
+ from .models import PRReviewFinding, ReviewSeverity
+except (ImportError, ValueError, SystemError):
+ # For direct module loading in tests
+ from models import PRReviewFinding, ReviewSeverity
+
+
+class FindingValidator:
+ """Validates and filters AI-generated PR review findings."""
+
+ # Vague patterns that indicate low-quality findings
+ VAGUE_PATTERNS = [
+ "could be improved",
+ "consider using",
+ "might want to",
+ "you may want",
+ "it would be better",
+ "possibly consider",
+ "perhaps use",
+ "potentially add",
+ "you should consider",
+ "it might be good",
+ ]
+
+ # Generic suggestions without specifics
+ GENERIC_PATTERNS = [
+ "improve this",
+ "fix this",
+ "change this",
+ "update this",
+ "refactor this",
+ "review this",
+ ]
+
+ # Minimum lengths for quality checks
+ MIN_DESCRIPTION_LENGTH = 30
+ MIN_SUGGESTED_FIX_LENGTH = 20
+ MIN_TITLE_LENGTH = 10
+
+ # Confidence thresholds
+ BASE_CONFIDENCE = 0.5
+ MIN_ACTIONABILITY_SCORE = 0.6
+ HIGH_ACTIONABILITY_SCORE = 0.8
+
+ def __init__(self, project_dir: Path, changed_files: dict[str, str]):
+ """
+ Initialize validator.
+
+ Args:
+ project_dir: Root directory of the project
+ changed_files: Mapping of file paths to their content
+ """
+ self.project_dir = Path(project_dir)
+ self.changed_files = changed_files
+
+ def validate_findings(
+ self, findings: list[PRReviewFinding]
+ ) -> list[PRReviewFinding]:
+ """
+ Validate all findings, removing invalid ones and enhancing valid ones.
+
+ Args:
+ findings: List of findings to validate
+
+ Returns:
+ List of validated and enhanced findings
+ """
+ validated = []
+
+ for finding in findings:
+ if self._is_valid(finding):
+ enhanced = self._enhance(finding)
+ validated.append(enhanced)
+
+ return validated
+
+ def _is_valid(self, finding: PRReviewFinding) -> bool:
+ """
+ Check if a finding is valid.
+
+ Args:
+ finding: Finding to validate
+
+ Returns:
+ True if finding is valid, False otherwise
+ """
+ # Check basic field requirements
+ if not finding.file or not finding.title or not finding.description:
+ return False
+
+ # Check title length
+ if len(finding.title.strip()) < self.MIN_TITLE_LENGTH:
+ return False
+
+ # Check description length
+ if len(finding.description.strip()) < self.MIN_DESCRIPTION_LENGTH:
+ return False
+
+ # Check if file exists in changed files
+ if finding.file not in self.changed_files:
+ return False
+
+ # Verify line number
+ if not self._verify_line_number(finding):
+ # Try to auto-correct
+ corrected = self._auto_correct_line_number(finding)
+ if not self._verify_line_number(corrected):
+ return False
+ # Update the finding with corrected line
+ finding.line = corrected.line
+
+ # Check for false positives
+ if self._is_false_positive(finding):
+ return False
+
+ # Check confidence threshold
+ if not self._meets_confidence_threshold(finding):
+ return False
+
+ return True
+
+ def _verify_line_number(self, finding: PRReviewFinding) -> bool:
+ """
+ Verify the line number actually exists and is relevant.
+
+ Args:
+ finding: Finding to verify
+
+ Returns:
+ True if line number is valid, False otherwise
+ """
+ file_content = self.changed_files.get(finding.file)
+ if not file_content:
+ return False
+
+ lines = file_content.split("\n")
+
+ # Check bounds
+ if finding.line > len(lines) or finding.line < 1:
+ return False
+
+ # Check if the line contains something related to the finding
+ line_content = lines[finding.line - 1]
+ return self._is_line_relevant(line_content, finding)
+
+ def _is_line_relevant(self, line_content: str, finding: PRReviewFinding) -> bool:
+ """
+ Check if a line is relevant to the finding.
+
+ Args:
+ line_content: Content of the line
+ finding: Finding to check against
+
+ Returns:
+ True if line is relevant, False otherwise
+ """
+ # Empty or whitespace-only lines are not relevant
+ if not line_content.strip():
+ return False
+
+ # Extract key terms from finding
+ key_terms = self._extract_key_terms(finding)
+
+ # Check if any key terms appear in the line (case-insensitive)
+ line_lower = line_content.lower()
+ for term in key_terms:
+ if term.lower() in line_lower:
+ return True
+
+ # For security findings, check for common security-related patterns
+ if finding.category.value == "security":
+ security_patterns = [
+ r"password",
+ r"token",
+ r"secret",
+ r"api[_-]?key",
+ r"auth",
+ r"credential",
+ r"eval\(",
+ r"exec\(",
+ r"\.html\(",
+ r"innerHTML",
+ r"dangerouslySetInnerHTML",
+ r"__import__",
+ r"subprocess",
+ r"shell=True",
+ ]
+ for pattern in security_patterns:
+ if re.search(pattern, line_lower):
+ return True
+
+ return False
+
+ def _extract_key_terms(self, finding: PRReviewFinding) -> list[str]:
+ """
+ Extract key terms from finding for relevance checking.
+
+ Args:
+ finding: Finding to extract terms from
+
+ Returns:
+ List of key terms
+ """
+ terms = []
+
+ # Extract from title
+ title_words = re.findall(r"\b\w{4,}\b", finding.title)
+ terms.extend(title_words)
+
+ # Extract code-like terms from description
+ code_pattern = r"`([^`]+)`"
+ code_matches = re.findall(code_pattern, finding.description)
+ terms.extend(code_matches)
+
+ # Extract from suggested fix if available
+ if finding.suggested_fix:
+ fix_matches = re.findall(code_pattern, finding.suggested_fix)
+ terms.extend(fix_matches)
+
+ # Remove common words
+ common_words = {
+ "this",
+ "that",
+ "with",
+ "from",
+ "have",
+ "should",
+ "could",
+ "would",
+ "using",
+ "used",
+ }
+ terms = [t for t in terms if t.lower() not in common_words]
+
+ return list(set(terms)) # Remove duplicates
+
+ def _auto_correct_line_number(self, finding: PRReviewFinding) -> PRReviewFinding:
+ """
+ Try to find the correct line if the specified one is wrong.
+
+ Args:
+ finding: Finding with potentially incorrect line number
+
+ Returns:
+ Finding with corrected line number (or original if correction failed)
+ """
+ file_content = self.changed_files.get(finding.file, "")
+ if not file_content:
+ return finding
+
+ lines = file_content.split("\n")
+
+ # Search nearby lines (±10) for relevant content
+ for offset in range(0, 11):
+ for direction in [1, -1]:
+ check_line = finding.line + (offset * direction)
+
+ # Skip if out of bounds
+ if check_line < 1 or check_line > len(lines):
+ continue
+
+ # Check if this line is relevant
+ if self._is_line_relevant(lines[check_line - 1], finding):
+ finding.line = check_line
+ return finding
+
+ # If no nearby line found, try searching the entire file for best match
+ key_terms = self._extract_key_terms(finding)
+ best_match_line = 0
+ best_match_score = 0
+
+ for i, line in enumerate(lines, start=1):
+ score = sum(1 for term in key_terms if term.lower() in line.lower())
+ if score > best_match_score:
+ best_match_score = score
+ best_match_line = i
+
+ if best_match_score > 0:
+ finding.line = best_match_line
+
+ return finding
+
+ def _is_false_positive(self, finding: PRReviewFinding) -> bool:
+ """
+ Detect likely false positives.
+
+ Args:
+ finding: Finding to check
+
+ Returns:
+ True if likely a false positive, False otherwise
+ """
+ description_lower = finding.description.lower()
+
+ # Check for vague descriptions
+ for pattern in self.VAGUE_PATTERNS:
+ if pattern in description_lower:
+ # Vague low/medium findings are likely FPs
+ if finding.severity in [ReviewSeverity.LOW, ReviewSeverity.MEDIUM]:
+ return True
+
+ # Check for generic suggestions
+ for pattern in self.GENERIC_PATTERNS:
+ if pattern in description_lower:
+ if finding.severity == ReviewSeverity.LOW:
+ return True
+
+ # Check for generic suggestions without specifics
+ if (
+ not finding.suggested_fix
+ or len(finding.suggested_fix) < self.MIN_SUGGESTED_FIX_LENGTH
+ ):
+ if finding.severity == ReviewSeverity.LOW:
+ return True
+
+ # Check for style findings without clear justification
+ if finding.category.value == "style":
+ # Style findings should have good suggestions
+ if not finding.suggested_fix or len(finding.suggested_fix) < 30:
+ return True
+
+ # Check for overly short descriptions
+ if len(finding.description) < 50 and finding.severity == ReviewSeverity.LOW:
+ return True
+
+ return False
+
+ def _score_actionability(self, finding: PRReviewFinding) -> float:
+ """
+ Score how actionable a finding is (0.0 to 1.0).
+
+ Args:
+ finding: Finding to score
+
+ Returns:
+ Actionability score between 0.0 and 1.0
+ """
+ score = self.BASE_CONFIDENCE
+
+ # Has specific file and line
+ if finding.file and finding.line:
+ score += 0.1
+
+ # Has line range (more specific)
+ if finding.end_line and finding.end_line > finding.line:
+ score += 0.05
+
+ # Has suggested fix
+ if finding.suggested_fix:
+ if len(finding.suggested_fix) > self.MIN_SUGGESTED_FIX_LENGTH:
+ score += 0.15
+ if len(finding.suggested_fix) > 50:
+ score += 0.1
+
+ # Has clear description
+ if len(finding.description) > 50:
+ score += 0.1
+ if len(finding.description) > 100:
+ score += 0.05
+
+ # Is marked as fixable
+ if finding.fixable:
+ score += 0.1
+
+ # Severity impacts actionability
+ severity_scores = {
+ ReviewSeverity.CRITICAL: 0.15,
+ ReviewSeverity.HIGH: 0.1,
+ ReviewSeverity.MEDIUM: 0.05,
+ ReviewSeverity.LOW: 0.0,
+ }
+ score += severity_scores.get(finding.severity, 0.0)
+
+ # Security and test findings are generally more actionable
+ if finding.category.value in ["security", "test"]:
+ score += 0.1
+
+ # Has code examples in description or fix
+ code_pattern = r"```[\s\S]*?```|`[^`]+`"
+ if re.search(code_pattern, finding.description):
+ score += 0.05
+ if finding.suggested_fix and re.search(code_pattern, finding.suggested_fix):
+ score += 0.05
+
+ return min(score, 1.0)
+
+ def _meets_confidence_threshold(self, finding: PRReviewFinding) -> bool:
+ """
+ Check if finding meets confidence threshold.
+
+ Args:
+ finding: Finding to check
+
+ Returns:
+ True if meets threshold, False otherwise
+ """
+ # If finding has explicit confidence field, use it
+ if hasattr(finding, "confidence") and finding.confidence:
+ return finding.confidence >= self.HIGH_ACTIONABILITY_SCORE
+
+ # Otherwise, use actionability score as proxy for confidence
+ actionability = self._score_actionability(finding)
+
+ # Critical/high severity findings have lower threshold
+ if finding.severity in [ReviewSeverity.CRITICAL, ReviewSeverity.HIGH]:
+ return actionability >= 0.5
+
+ # Other findings need higher threshold
+ return actionability >= self.MIN_ACTIONABILITY_SCORE
+
+ def _enhance(self, finding: PRReviewFinding) -> PRReviewFinding:
+ """
+ Enhance a validated finding with additional metadata.
+
+ Args:
+ finding: Finding to enhance
+
+ Returns:
+ Enhanced finding
+ """
+ # Add actionability score as confidence if not already present
+ if not hasattr(finding, "confidence") or not finding.confidence:
+ actionability = self._score_actionability(finding)
+ # Add as custom attribute (not in dataclass, but accessible)
+ finding.__dict__["confidence"] = actionability
+
+ # Ensure fixable is set correctly based on having a suggested fix
+ if (
+ finding.suggested_fix
+ and len(finding.suggested_fix) > self.MIN_SUGGESTED_FIX_LENGTH
+ ):
+ finding.fixable = True
+
+ # Clean up whitespace in fields
+ finding.title = finding.title.strip()
+ finding.description = finding.description.strip()
+ if finding.suggested_fix:
+ finding.suggested_fix = finding.suggested_fix.strip()
+
+ return finding
+
+ def get_validation_stats(
+ self,
+ original_findings: list[PRReviewFinding],
+ validated_findings: list[PRReviewFinding],
+ ) -> dict[str, Any]:
+ """
+ Get statistics about the validation process.
+
+ Args:
+ original_findings: Original list of findings
+ validated_findings: Validated list of findings
+
+ Returns:
+ Dictionary with validation statistics
+ """
+ total = len(original_findings)
+ kept = len(validated_findings)
+ filtered = total - kept
+
+ # Count by severity
+ severity_counts = {
+ "critical": 0,
+ "high": 0,
+ "medium": 0,
+ "low": 0,
+ }
+
+ # Count by category
+ category_counts = {
+ "security": 0,
+ "quality": 0,
+ "style": 0,
+ "test": 0,
+ "docs": 0,
+ "pattern": 0,
+ "performance": 0,
+ }
+
+ # Calculate average actionability
+ total_actionability = 0.0
+
+ for finding in validated_findings:
+ severity_counts[finding.severity.value] += 1
+ category_counts[finding.category.value] += 1
+
+ # Get actionability score
+ if hasattr(finding, "confidence") and finding.confidence:
+ total_actionability += finding.confidence
+ else:
+ total_actionability += self._score_actionability(finding)
+
+ avg_actionability = total_actionability / kept if kept > 0 else 0.0
+
+ return {
+ "total_findings": total,
+ "kept_findings": kept,
+ "filtered_findings": filtered,
+ "filter_rate": filtered / total if total > 0 else 0.0,
+ "severity_distribution": severity_counts,
+ "category_distribution": category_counts,
+ "average_actionability": avg_actionability,
+ "fixable_count": sum(1 for f in validated_findings if f.fixable),
+ }
diff --git a/apps/backend/runners/github/override.py b/apps/backend/runners/github/override.py
new file mode 100644
index 00000000..fab53cb4
--- /dev/null
+++ b/apps/backend/runners/github/override.py
@@ -0,0 +1,835 @@
+"""
+GitHub Automation Override System
+=================================
+
+Handles user overrides, cancellations, and undo operations:
+- Grace period for label-triggered actions
+- Comment command processing (/cancel-autofix, /undo-last)
+- One-click override buttons (Not spam, Not duplicate)
+- Override history for audit and learning
+"""
+
+from __future__ import annotations
+
+import json
+import re
+from dataclasses import dataclass, field
+from datetime import datetime, timedelta, timezone
+from enum import Enum
+from pathlib import Path
+from typing import Any
+
+try:
+ from .audit import ActorType, AuditLogger
+ from .file_lock import locked_json_update
+except (ImportError, ValueError, SystemError):
+ from audit import ActorType, AuditLogger
+ from file_lock import locked_json_update
+
+
+class OverrideType(str, Enum):
+ """Types of override actions."""
+
+ CANCEL_AUTOFIX = "cancel_autofix"
+ NOT_SPAM = "not_spam"
+ NOT_DUPLICATE = "not_duplicate"
+ NOT_FEATURE_CREEP = "not_feature_creep"
+ UNDO_LAST = "undo_last"
+ FORCE_RETRY = "force_retry"
+ SKIP_REVIEW = "skip_review"
+ APPROVE_SPEC = "approve_spec"
+ REJECT_SPEC = "reject_spec"
+
+
+class CommandType(str, Enum):
+ """Recognized comment commands."""
+
+ CANCEL_AUTOFIX = "/cancel-autofix"
+ UNDO_LAST = "/undo-last"
+ FORCE_RETRY = "/force-retry"
+ SKIP_REVIEW = "/skip-review"
+ APPROVE = "/approve"
+ REJECT = "/reject"
+ NOT_SPAM = "/not-spam"
+ NOT_DUPLICATE = "/not-duplicate"
+ STATUS = "/status"
+ HELP = "/help"
+
+
+@dataclass
+class OverrideRecord:
+ """Record of an override action."""
+
+ id: str
+ override_type: OverrideType
+ issue_number: int | None
+ pr_number: int | None
+ repo: str
+ actor: str # Username who performed override
+ reason: str | None
+ original_state: str | None
+ new_state: str | None
+ created_at: str = field(
+ default_factory=lambda: datetime.now(timezone.utc).isoformat()
+ )
+ metadata: dict[str, Any] = field(default_factory=dict)
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "id": self.id,
+ "override_type": self.override_type.value,
+ "issue_number": self.issue_number,
+ "pr_number": self.pr_number,
+ "repo": self.repo,
+ "actor": self.actor,
+ "reason": self.reason,
+ "original_state": self.original_state,
+ "new_state": self.new_state,
+ "created_at": self.created_at,
+ "metadata": self.metadata,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict[str, Any]) -> OverrideRecord:
+ return cls(
+ id=data["id"],
+ override_type=OverrideType(data["override_type"]),
+ issue_number=data.get("issue_number"),
+ pr_number=data.get("pr_number"),
+ repo=data["repo"],
+ actor=data["actor"],
+ reason=data.get("reason"),
+ original_state=data.get("original_state"),
+ new_state=data.get("new_state"),
+ created_at=data.get("created_at", datetime.now(timezone.utc).isoformat()),
+ metadata=data.get("metadata", {}),
+ )
+
+
+@dataclass
+class GracePeriodEntry:
+ """Entry tracking grace period for an automation trigger."""
+
+ issue_number: int
+ trigger_label: str
+ triggered_by: str
+ triggered_at: str
+ expires_at: str
+ cancelled: bool = False
+ cancelled_by: str | None = None
+ cancelled_at: str | None = None
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "issue_number": self.issue_number,
+ "trigger_label": self.trigger_label,
+ "triggered_by": self.triggered_by,
+ "triggered_at": self.triggered_at,
+ "expires_at": self.expires_at,
+ "cancelled": self.cancelled,
+ "cancelled_by": self.cancelled_by,
+ "cancelled_at": self.cancelled_at,
+ }
+
+ @classmethod
+ def from_dict(cls, data: dict[str, Any]) -> GracePeriodEntry:
+ return cls(
+ issue_number=data["issue_number"],
+ trigger_label=data["trigger_label"],
+ triggered_by=data["triggered_by"],
+ triggered_at=data["triggered_at"],
+ expires_at=data["expires_at"],
+ cancelled=data.get("cancelled", False),
+ cancelled_by=data.get("cancelled_by"),
+ cancelled_at=data.get("cancelled_at"),
+ )
+
+ def is_in_grace_period(self) -> bool:
+ """Check if still within grace period."""
+ if self.cancelled:
+ return False
+ expires = datetime.fromisoformat(self.expires_at)
+ return datetime.now(timezone.utc) < expires
+
+ def time_remaining(self) -> timedelta:
+ """Get remaining time in grace period."""
+ expires = datetime.fromisoformat(self.expires_at)
+ remaining = expires - datetime.now(timezone.utc)
+ return max(remaining, timedelta(0))
+
+
+@dataclass
+class ParsedCommand:
+ """Parsed comment command."""
+
+ command: CommandType
+ args: list[str]
+ raw_text: str
+ author: str
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "command": self.command.value,
+ "args": self.args,
+ "raw_text": self.raw_text,
+ "author": self.author,
+ }
+
+
+class OverrideManager:
+ """
+ Manages user overrides and cancellations.
+
+ Usage:
+ override_mgr = OverrideManager(github_dir=Path(".auto-claude/github"))
+
+ # Start grace period when label is added
+ grace = override_mgr.start_grace_period(
+ issue_number=123,
+ trigger_label="auto-fix",
+ triggered_by="username",
+ )
+
+ # Check if still in grace period before acting
+ if override_mgr.is_in_grace_period(123):
+ print("Still in grace period, waiting...")
+
+ # Process comment commands
+ cmd = override_mgr.parse_comment("/cancel-autofix", "username")
+ if cmd:
+ result = await override_mgr.execute_command(cmd, issue_number=123)
+ """
+
+ # Default grace period: 15 minutes
+ DEFAULT_GRACE_PERIOD_MINUTES = 15
+
+ def __init__(
+ self,
+ github_dir: Path,
+ grace_period_minutes: int = DEFAULT_GRACE_PERIOD_MINUTES,
+ audit_logger: AuditLogger | None = None,
+ ):
+ """
+ Initialize override manager.
+
+ Args:
+ github_dir: Directory for storing override state
+ grace_period_minutes: Grace period duration (default: 15 min)
+ audit_logger: Optional audit logger for recording overrides
+ """
+ self.github_dir = github_dir
+ self.override_dir = github_dir / "overrides"
+ self.override_dir.mkdir(parents=True, exist_ok=True)
+ self.grace_period_minutes = grace_period_minutes
+ self.audit_logger = audit_logger
+
+ # Command pattern for parsing
+ self._command_pattern = re.compile(
+ r"^\s*(/[a-z-]+)(?:\s+(.*))?$", re.IGNORECASE | re.MULTILINE
+ )
+
+ def _get_grace_file(self) -> Path:
+ """Get path to grace period tracking file."""
+ return self.override_dir / "grace_periods.json"
+
+ def _get_history_file(self) -> Path:
+ """Get path to override history file."""
+ return self.override_dir / "override_history.json"
+
+ def _generate_override_id(self) -> str:
+ """Generate unique override ID."""
+ import uuid
+
+ return f"ovr-{uuid.uuid4().hex[:8]}"
+
+ # =========================================================================
+ # GRACE PERIOD MANAGEMENT
+ # =========================================================================
+
+ def start_grace_period(
+ self,
+ issue_number: int,
+ trigger_label: str,
+ triggered_by: str,
+ grace_minutes: int | None = None,
+ ) -> GracePeriodEntry:
+ """
+ Start a grace period for an automation trigger.
+
+ Args:
+ issue_number: Issue that was triggered
+ trigger_label: Label that triggered automation
+ triggered_by: Username who added the label
+ grace_minutes: Override default grace period
+
+ Returns:
+ GracePeriodEntry tracking the grace period
+ """
+ minutes = grace_minutes or self.grace_period_minutes
+ now = datetime.now(timezone.utc)
+
+ entry = GracePeriodEntry(
+ issue_number=issue_number,
+ trigger_label=trigger_label,
+ triggered_by=triggered_by,
+ triggered_at=now.isoformat(),
+ expires_at=(now + timedelta(minutes=minutes)).isoformat(),
+ )
+
+ self._save_grace_entry(entry)
+ return entry
+
+ def _save_grace_entry(self, entry: GracePeriodEntry) -> None:
+ """Save grace period entry to file."""
+ grace_file = self._get_grace_file()
+
+ def update_grace(data: dict | None) -> dict:
+ if data is None:
+ data = {"entries": {}}
+ data["entries"][str(entry.issue_number)] = entry.to_dict()
+ data["last_updated"] = datetime.now(timezone.utc).isoformat()
+ return data
+
+ import asyncio
+
+ asyncio.run(locked_json_update(grace_file, update_grace, timeout=5.0))
+
+ def get_grace_period(self, issue_number: int) -> GracePeriodEntry | None:
+ """Get grace period entry for an issue."""
+ grace_file = self._get_grace_file()
+ if not grace_file.exists():
+ return None
+
+ with open(grace_file) as f:
+ data = json.load(f)
+
+ entry_data = data.get("entries", {}).get(str(issue_number))
+ if entry_data:
+ return GracePeriodEntry.from_dict(entry_data)
+ return None
+
+ def is_in_grace_period(self, issue_number: int) -> bool:
+ """Check if issue is still in grace period."""
+ entry = self.get_grace_period(issue_number)
+ if entry:
+ return entry.is_in_grace_period()
+ return False
+
+ def cancel_grace_period(
+ self,
+ issue_number: int,
+ cancelled_by: str,
+ ) -> bool:
+ """
+ Cancel an active grace period.
+
+ Args:
+ issue_number: Issue to cancel
+ cancelled_by: Username cancelling
+
+ Returns:
+ True if successfully cancelled, False if no active grace period
+ """
+ entry = self.get_grace_period(issue_number)
+ if not entry or not entry.is_in_grace_period():
+ return False
+
+ entry.cancelled = True
+ entry.cancelled_by = cancelled_by
+ entry.cancelled_at = datetime.now(timezone.utc).isoformat()
+
+ self._save_grace_entry(entry)
+ return True
+
+ # =========================================================================
+ # COMMAND PARSING
+ # =========================================================================
+
+ def parse_comment(self, comment_body: str, author: str) -> ParsedCommand | None:
+ """
+ Parse a comment for recognized commands.
+
+ Args:
+ comment_body: Full comment text
+ author: Comment author username
+
+ Returns:
+ ParsedCommand if command found, None otherwise
+ """
+ match = self._command_pattern.search(comment_body)
+ if not match:
+ return None
+
+ cmd_text = match.group(1).lower()
+ args_text = match.group(2) or ""
+ args = args_text.split() if args_text else []
+
+ # Map to command type
+ command_map = {
+ "/cancel-autofix": CommandType.CANCEL_AUTOFIX,
+ "/undo-last": CommandType.UNDO_LAST,
+ "/force-retry": CommandType.FORCE_RETRY,
+ "/skip-review": CommandType.SKIP_REVIEW,
+ "/approve": CommandType.APPROVE,
+ "/reject": CommandType.REJECT,
+ "/not-spam": CommandType.NOT_SPAM,
+ "/not-duplicate": CommandType.NOT_DUPLICATE,
+ "/status": CommandType.STATUS,
+ "/help": CommandType.HELP,
+ }
+
+ command = command_map.get(cmd_text)
+ if not command:
+ return None
+
+ return ParsedCommand(
+ command=command,
+ args=args,
+ raw_text=comment_body,
+ author=author,
+ )
+
+ def get_help_text(self) -> str:
+ """Get help text for available commands."""
+ return """**Available Commands:**
+
+| Command | Description |
+|---------|-------------|
+| `/cancel-autofix` | Cancel pending auto-fix (works during grace period) |
+| `/undo-last` | Undo the most recent automation action |
+| `/force-retry` | Retry a failed operation |
+| `/skip-review` | Skip AI review for this PR |
+| `/approve` | Approve pending spec/action |
+| `/reject` | Reject pending spec/action |
+| `/not-spam` | Override spam classification |
+| `/not-duplicate` | Override duplicate classification |
+| `/status` | Show current automation status |
+| `/help` | Show this help message |
+"""
+
+ # =========================================================================
+ # OVERRIDE EXECUTION
+ # =========================================================================
+
+ async def execute_command(
+ self,
+ command: ParsedCommand,
+ issue_number: int | None = None,
+ pr_number: int | None = None,
+ repo: str = "",
+ current_state: str | None = None,
+ ) -> dict[str, Any]:
+ """
+ Execute a parsed command.
+
+ Args:
+ command: Parsed command to execute
+ issue_number: Issue number if applicable
+ pr_number: PR number if applicable
+ repo: Repository in owner/repo format
+ current_state: Current state of the item
+
+ Returns:
+ Result dict with success status and message
+ """
+ result = {
+ "success": False,
+ "message": "",
+ "override_id": None,
+ }
+
+ if command.command == CommandType.HELP:
+ result["success"] = True
+ result["message"] = self.get_help_text()
+ return result
+
+ if command.command == CommandType.STATUS:
+ # Return status info
+ result["success"] = True
+ result["message"] = await self._get_status(issue_number, pr_number)
+ return result
+
+ # Commands that require issue/PR context
+ if command.command == CommandType.CANCEL_AUTOFIX:
+ if not issue_number:
+ result["message"] = "Issue number required for /cancel-autofix"
+ return result
+
+ # Check grace period
+ if self.is_in_grace_period(issue_number):
+ if self.cancel_grace_period(issue_number, command.author):
+ result["success"] = True
+ result["message"] = f"Auto-fix cancelled for issue #{issue_number}"
+
+ # Record override
+ override = self._record_override(
+ override_type=OverrideType.CANCEL_AUTOFIX,
+ issue_number=issue_number,
+ repo=repo,
+ actor=command.author,
+ reason="Cancelled during grace period",
+ original_state=current_state,
+ new_state="cancelled",
+ )
+ result["override_id"] = override.id
+ else:
+ result["message"] = "No active grace period to cancel"
+ else:
+ # Try to cancel even if past grace period
+ result["success"] = True
+ result["message"] = (
+ f"Auto-fix cancellation requested for issue #{issue_number}. "
+ f"Note: Grace period has expired."
+ )
+
+ override = self._record_override(
+ override_type=OverrideType.CANCEL_AUTOFIX,
+ issue_number=issue_number,
+ repo=repo,
+ actor=command.author,
+ reason="Cancelled after grace period",
+ original_state=current_state,
+ new_state="cancelled",
+ )
+ result["override_id"] = override.id
+
+ elif command.command == CommandType.NOT_SPAM:
+ result = self._handle_triage_override(
+ OverrideType.NOT_SPAM,
+ issue_number,
+ repo,
+ command.author,
+ current_state,
+ )
+
+ elif command.command == CommandType.NOT_DUPLICATE:
+ result = self._handle_triage_override(
+ OverrideType.NOT_DUPLICATE,
+ issue_number,
+ repo,
+ command.author,
+ current_state,
+ )
+
+ elif command.command == CommandType.FORCE_RETRY:
+ result["success"] = True
+ result["message"] = (
+ f"Retry requested for issue #{issue_number or pr_number}"
+ )
+
+ override = self._record_override(
+ override_type=OverrideType.FORCE_RETRY,
+ issue_number=issue_number,
+ pr_number=pr_number,
+ repo=repo,
+ actor=command.author,
+ original_state=current_state,
+ new_state="pending",
+ )
+ result["override_id"] = override.id
+
+ elif command.command == CommandType.UNDO_LAST:
+ result = await self._handle_undo_last(
+ issue_number, pr_number, repo, command.author
+ )
+
+ elif command.command == CommandType.APPROVE:
+ result["success"] = True
+ result["message"] = "Approved"
+
+ override = self._record_override(
+ override_type=OverrideType.APPROVE_SPEC,
+ issue_number=issue_number,
+ pr_number=pr_number,
+ repo=repo,
+ actor=command.author,
+ original_state=current_state,
+ new_state="approved",
+ )
+ result["override_id"] = override.id
+
+ elif command.command == CommandType.REJECT:
+ result["success"] = True
+ result["message"] = "Rejected"
+
+ override = self._record_override(
+ override_type=OverrideType.REJECT_SPEC,
+ issue_number=issue_number,
+ pr_number=pr_number,
+ repo=repo,
+ actor=command.author,
+ original_state=current_state,
+ new_state="rejected",
+ )
+ result["override_id"] = override.id
+
+ elif command.command == CommandType.SKIP_REVIEW:
+ result["success"] = True
+ result["message"] = f"AI review skipped for PR #{pr_number}"
+
+ override = self._record_override(
+ override_type=OverrideType.SKIP_REVIEW,
+ pr_number=pr_number,
+ repo=repo,
+ actor=command.author,
+ original_state=current_state,
+ new_state="skipped",
+ )
+ result["override_id"] = override.id
+
+ return result
+
+ def _handle_triage_override(
+ self,
+ override_type: OverrideType,
+ issue_number: int | None,
+ repo: str,
+ actor: str,
+ current_state: str | None,
+ ) -> dict[str, Any]:
+ """Handle triage classification overrides."""
+ result = {"success": False, "message": "", "override_id": None}
+
+ if not issue_number:
+ result["message"] = "Issue number required"
+ return result
+
+ override = self._record_override(
+ override_type=override_type,
+ issue_number=issue_number,
+ repo=repo,
+ actor=actor,
+ original_state=current_state,
+ new_state="feature", # Default to feature when overriding spam/duplicate
+ )
+
+ result["success"] = True
+ result["message"] = f"Classification overridden for issue #{issue_number}"
+ result["override_id"] = override.id
+
+ return result
+
+ async def _handle_undo_last(
+ self,
+ issue_number: int | None,
+ pr_number: int | None,
+ repo: str,
+ actor: str,
+ ) -> dict[str, Any]:
+ """Handle undo last action command."""
+ result = {"success": False, "message": "", "override_id": None}
+
+ # Find most recent action for this issue/PR
+ history = self.get_override_history(
+ issue_number=issue_number,
+ pr_number=pr_number,
+ limit=1,
+ )
+
+ if not history:
+ result["message"] = "No previous action to undo"
+ return result
+
+ last_action = history[0]
+
+ # Record the undo
+ override = self._record_override(
+ override_type=OverrideType.UNDO_LAST,
+ issue_number=issue_number,
+ pr_number=pr_number,
+ repo=repo,
+ actor=actor,
+ original_state=last_action.new_state,
+ new_state=last_action.original_state,
+ metadata={"undone_action_id": last_action.id},
+ )
+
+ result["success"] = True
+ result["message"] = f"Undone: {last_action.override_type.value}"
+ result["override_id"] = override.id
+
+ return result
+
+ async def _get_status(
+ self,
+ issue_number: int | None,
+ pr_number: int | None,
+ ) -> str:
+ """Get status information for an issue/PR."""
+ lines = ["**Automation Status:**\n"]
+
+ if issue_number:
+ grace = self.get_grace_period(issue_number)
+ if grace:
+ if grace.is_in_grace_period():
+ remaining = grace.time_remaining()
+ lines.append(
+ f"- Issue #{issue_number}: In grace period "
+ f"({int(remaining.total_seconds() / 60)} min remaining)"
+ )
+ elif grace.cancelled:
+ lines.append(
+ f"- Issue #{issue_number}: Cancelled by {grace.cancelled_by}"
+ )
+ else:
+ lines.append(f"- Issue #{issue_number}: Grace period expired")
+
+ # Get recent overrides
+ history = self.get_override_history(
+ issue_number=issue_number, pr_number=pr_number, limit=5
+ )
+ if history:
+ lines.append("\n**Recent Actions:**")
+ for record in history:
+ lines.append(f"- {record.override_type.value} by {record.actor}")
+
+ if len(lines) == 1:
+ lines.append("No automation activity found.")
+
+ return "\n".join(lines)
+
+ # =========================================================================
+ # OVERRIDE HISTORY
+ # =========================================================================
+
+ def _record_override(
+ self,
+ override_type: OverrideType,
+ repo: str,
+ actor: str,
+ issue_number: int | None = None,
+ pr_number: int | None = None,
+ reason: str | None = None,
+ original_state: str | None = None,
+ new_state: str | None = None,
+ metadata: dict[str, Any] | None = None,
+ ) -> OverrideRecord:
+ """Record an override action."""
+ record = OverrideRecord(
+ id=self._generate_override_id(),
+ override_type=override_type,
+ issue_number=issue_number,
+ pr_number=pr_number,
+ repo=repo,
+ actor=actor,
+ reason=reason,
+ original_state=original_state,
+ new_state=new_state,
+ metadata=metadata or {},
+ )
+
+ self._save_override_record(record)
+
+ # Log to audit if available
+ if self.audit_logger:
+ ctx = self.audit_logger.start_operation(
+ actor_type=ActorType.USER,
+ actor_id=actor,
+ repo=repo,
+ issue_number=issue_number,
+ pr_number=pr_number,
+ )
+ self.audit_logger.log_override(
+ ctx,
+ override_type=override_type.value,
+ original_action=original_state or "unknown",
+ actor_id=actor,
+ )
+
+ return record
+
+ def _save_override_record(self, record: OverrideRecord) -> None:
+ """Save override record to history file."""
+ history_file = self._get_history_file()
+
+ def update_history(data: dict | None) -> dict:
+ if data is None:
+ data = {"records": []}
+ data["records"].insert(0, record.to_dict())
+ # Keep last 1000 records
+ data["records"] = data["records"][:1000]
+ data["last_updated"] = datetime.now(timezone.utc).isoformat()
+ return data
+
+ import asyncio
+
+ asyncio.run(locked_json_update(history_file, update_history, timeout=5.0))
+
+ def get_override_history(
+ self,
+ issue_number: int | None = None,
+ pr_number: int | None = None,
+ override_type: OverrideType | None = None,
+ limit: int = 50,
+ ) -> list[OverrideRecord]:
+ """
+ Get override history with optional filters.
+
+ Args:
+ issue_number: Filter by issue number
+ pr_number: Filter by PR number
+ override_type: Filter by override type
+ limit: Maximum records to return
+
+ Returns:
+ List of OverrideRecord objects, most recent first
+ """
+ history_file = self._get_history_file()
+ if not history_file.exists():
+ return []
+
+ with open(history_file) as f:
+ data = json.load(f)
+
+ records = []
+ for record_data in data.get("records", []):
+ # Apply filters
+ if issue_number and record_data.get("issue_number") != issue_number:
+ continue
+ if pr_number and record_data.get("pr_number") != pr_number:
+ continue
+ if (
+ override_type
+ and record_data.get("override_type") != override_type.value
+ ):
+ continue
+
+ records.append(OverrideRecord.from_dict(record_data))
+ if len(records) >= limit:
+ break
+
+ return records
+
+ def get_override_statistics(
+ self,
+ repo: str | None = None,
+ ) -> dict[str, Any]:
+ """Get aggregate statistics about overrides."""
+ history_file = self._get_history_file()
+ if not history_file.exists():
+ return {"total": 0, "by_type": {}, "by_actor": {}}
+
+ with open(history_file) as f:
+ data = json.load(f)
+
+ stats = {
+ "total": 0,
+ "by_type": {},
+ "by_actor": {},
+ }
+
+ for record_data in data.get("records", []):
+ if repo and record_data.get("repo") != repo:
+ continue
+
+ stats["total"] += 1
+
+ # Count by type
+ otype = record_data.get("override_type", "unknown")
+ stats["by_type"][otype] = stats["by_type"].get(otype, 0) + 1
+
+ # Count by actor
+ actor = record_data.get("actor", "unknown")
+ stats["by_actor"][actor] = stats["by_actor"].get(actor, 0) + 1
+
+ return stats
diff --git a/apps/backend/runners/github/permissions.py b/apps/backend/runners/github/permissions.py
new file mode 100644
index 00000000..bace80e4
--- /dev/null
+++ b/apps/backend/runners/github/permissions.py
@@ -0,0 +1,473 @@
+"""
+GitHub Permission and Authorization System
+==========================================
+
+Verifies who can trigger automation actions and validates token permissions.
+
+Key features:
+- Label-adder verification (who added the trigger label)
+- Role-based access control (OWNER, MEMBER, COLLABORATOR)
+- Token scope validation (fail fast if insufficient)
+- Organization/team membership checks
+- Permission denial logging with actor info
+"""
+
+from __future__ import annotations
+
+import logging
+from dataclasses import dataclass
+from typing import Literal
+
+logger = logging.getLogger(__name__)
+
+
+# GitHub permission roles
+GitHubRole = Literal["OWNER", "MEMBER", "COLLABORATOR", "CONTRIBUTOR", "NONE"]
+
+
+@dataclass
+class PermissionCheckResult:
+ """Result of a permission check."""
+
+ allowed: bool
+ username: str
+ role: GitHubRole
+ reason: str | None = None
+
+
+class PermissionError(Exception):
+ """Raised when permission checks fail."""
+
+ pass
+
+
+class GitHubPermissionChecker:
+ """
+ Verifies permissions for GitHub automation actions.
+
+ Required token scopes:
+ - repo: Full control of private repositories
+ - read:org: Read org and team membership (for org repos)
+
+ Usage:
+ checker = GitHubPermissionChecker(
+ gh_client=gh_client,
+ repo="owner/repo",
+ allowed_roles=["OWNER", "MEMBER"]
+ )
+
+ # Check who added a label
+ username, role = await checker.check_label_adder(123, "auto-fix")
+
+ # Verify if user can trigger auto-fix
+ result = await checker.is_allowed_for_autofix(username)
+ """
+
+ # Required OAuth scopes for full functionality
+ REQUIRED_SCOPES = ["repo", "read:org"]
+
+ # Minimum required scopes (repo only, for non-org repos)
+ MINIMUM_SCOPES = ["repo"]
+
+ def __init__(
+ self,
+ gh_client, # GitHubAPIClient from runner.py
+ repo: str,
+ allowed_roles: list[str] | None = None,
+ allow_external_contributors: bool = False,
+ ):
+ """
+ Initialize permission checker.
+
+ Args:
+ gh_client: GitHub API client instance
+ repo: Repository in "owner/repo" format
+ allowed_roles: List of allowed roles (default: OWNER, MEMBER, COLLABORATOR)
+ allow_external_contributors: Allow users with no write access (default: False)
+ """
+ self.gh_client = gh_client
+ self.repo = repo
+ self.owner, self.repo_name = repo.split("/")
+
+ # Default to trusted roles if not specified
+ self.allowed_roles = allowed_roles or ["OWNER", "MEMBER", "COLLABORATOR"]
+ self.allow_external_contributors = allow_external_contributors
+
+ # Cache for user roles (avoid repeated API calls)
+ self._role_cache: dict[str, GitHubRole] = {}
+
+ logger.info(
+ f"Initialized permission checker for {repo} with allowed roles: {self.allowed_roles}"
+ )
+
+ async def verify_token_scopes(self) -> None:
+ """
+ Verify token has required scopes. Raises PermissionError if insufficient.
+
+ This should be called at startup to fail fast if permissions are inadequate.
+ Uses the gh CLI to verify authentication status.
+ """
+ logger.info("Verifying GitHub token and permissions...")
+
+ try:
+ # Verify we can access the repo (checks auth + repo access)
+ repo_info = await self.gh_client.api_get(f"/repos/{self.repo}")
+
+ if not repo_info:
+ raise PermissionError(
+ f"Cannot access repository {self.repo}. "
+ f"Check your token has 'repo' scope."
+ )
+
+ # Check if we have write access (needed for auto-fix)
+ permissions = repo_info.get("permissions", {})
+ has_push = permissions.get("push", False)
+ has_admin = permissions.get("admin", False)
+
+ if not (has_push or has_admin):
+ logger.warning(
+ f"Token does not have write access to {self.repo}. "
+ f"Auto-fix and PR creation will not work."
+ )
+
+ # For org repos, try to verify org access
+ owner_type = repo_info.get("owner", {}).get("type", "")
+ if owner_type == "Organization":
+ try:
+ await self.gh_client.api_get(f"/orgs/{self.owner}")
+ logger.info(f"✓ Have access to organization {self.owner}")
+ except Exception:
+ logger.warning(
+ f"Cannot access org {self.owner} API. "
+ f"Team membership checks will be limited. "
+ f"Consider adding 'read:org' scope."
+ )
+
+ logger.info(f"✓ Token verified for {self.repo} (push={has_push})")
+
+ except PermissionError:
+ raise
+ except Exception as e:
+ logger.error(f"Failed to verify token: {e}")
+ raise PermissionError(f"Could not verify token permissions: {e}")
+
+ async def check_label_adder(
+ self, issue_number: int, label: str
+ ) -> tuple[str, GitHubRole]:
+ """
+ Check who added a specific label to an issue.
+
+ Args:
+ issue_number: Issue number
+ label: Label name to check
+
+ Returns:
+ Tuple of (username, role) who added the label
+
+ Raises:
+ PermissionError: If label was not found or couldn't determine who added it
+ """
+ logger.info(f"Checking who added label '{label}' to issue #{issue_number}")
+
+ try:
+ # Get issue timeline events
+ events = await self.gh_client.api_get(
+ f"/repos/{self.repo}/issues/{issue_number}/events"
+ )
+
+ # Find most recent label addition event
+ for event in reversed(events):
+ if (
+ event.get("event") == "labeled"
+ and event.get("label", {}).get("name") == label
+ ):
+ actor = event.get("actor", {})
+ username = actor.get("login")
+
+ if not username:
+ raise PermissionError(
+ f"Could not determine who added label '{label}'"
+ )
+
+ # Get role for this user
+ role = await self.get_user_role(username)
+
+ logger.info(
+ f"Label '{label}' was added by {username} (role: {role})"
+ )
+ return username, role
+
+ raise PermissionError(
+ f"Label '{label}' not found in issue #{issue_number} events"
+ )
+
+ except Exception as e:
+ logger.error(f"Failed to check label adder: {e}")
+ raise PermissionError(f"Could not verify label adder: {e}")
+
+ async def get_user_role(self, username: str) -> GitHubRole:
+ """
+ Get a user's role in the repository.
+
+ Args:
+ username: GitHub username
+
+ Returns:
+ User's role (OWNER, MEMBER, COLLABORATOR, CONTRIBUTOR, NONE)
+
+ Note:
+ - OWNER: Repository owner or org owner
+ - MEMBER: Organization member (for org repos)
+ - COLLABORATOR: Has write access
+ - CONTRIBUTOR: Has contributed but no write access
+ - NONE: No relationship to repo
+ """
+ # Check cache first
+ if username in self._role_cache:
+ return self._role_cache[username]
+
+ logger.debug(f"Checking role for user: {username}")
+
+ try:
+ # Check if user is owner
+ if username.lower() == self.owner.lower():
+ role = "OWNER"
+ self._role_cache[username] = role
+ return role
+
+ # Check collaborator status (write access)
+ try:
+ permission = await self.gh_client.api_get(
+ f"/repos/{self.repo}/collaborators/{username}/permission"
+ )
+ permission_level = permission.get("permission", "none")
+
+ if permission_level in ["admin", "maintain", "write"]:
+ role = "COLLABORATOR"
+ self._role_cache[username] = role
+ return role
+
+ except Exception:
+ logger.debug(f"User {username} is not a collaborator")
+
+ # For organization repos, check org membership
+ try:
+ # Check if repo is owned by an org
+ repo_info = await self.gh_client.api_get(f"/repos/{self.repo}")
+ if repo_info.get("owner", {}).get("type") == "Organization":
+ # Check org membership
+ try:
+ await self.gh_client.api_get(
+ f"/orgs/{self.owner}/members/{username}"
+ )
+ role = "MEMBER"
+ self._role_cache[username] = role
+ return role
+ except Exception:
+ logger.debug(f"User {username} is not an org member")
+
+ except Exception:
+ logger.debug("Could not check org membership")
+
+ # Check if user has any contributions
+ try:
+ # This is a heuristic - check if user appears in contributors
+ contributors = await self.gh_client.api_get(
+ f"/repos/{self.repo}/contributors"
+ )
+ if any(c.get("login") == username for c in contributors):
+ role = "CONTRIBUTOR"
+ self._role_cache[username] = role
+ return role
+ except Exception:
+ logger.debug("Could not check contributor status")
+
+ # No relationship found
+ role = "NONE"
+ self._role_cache[username] = role
+ return role
+
+ except Exception as e:
+ logger.error(f"Error checking user role for {username}: {e}")
+ # Fail safe - treat as no permission
+ return "NONE"
+
+ async def is_allowed_for_autofix(self, username: str) -> PermissionCheckResult:
+ """
+ Check if a user is allowed to trigger auto-fix.
+
+ Args:
+ username: GitHub username to check
+
+ Returns:
+ PermissionCheckResult with allowed status and details
+ """
+ logger.info(f"Checking auto-fix permission for user: {username}")
+
+ role = await self.get_user_role(username)
+
+ # Check if role is allowed
+ if role in self.allowed_roles:
+ logger.info(f"✓ User {username} ({role}) is allowed to trigger auto-fix")
+ return PermissionCheckResult(
+ allowed=True, username=username, role=role, reason=None
+ )
+
+ # Check if external contributors are allowed and user has contributed
+ if self.allow_external_contributors and role == "CONTRIBUTOR":
+ logger.info(
+ f"✓ User {username} (CONTRIBUTOR) is allowed via external contributor policy"
+ )
+ return PermissionCheckResult(
+ allowed=True, username=username, role=role, reason=None
+ )
+
+ # Permission denied
+ reason = (
+ f"User {username} has role '{role}', which is not in allowed roles: "
+ f"{self.allowed_roles}"
+ )
+
+ logger.warning(
+ f"✗ Auto-fix permission denied for {username}: {reason}",
+ extra={
+ "username": username,
+ "role": role,
+ "allowed_roles": self.allowed_roles,
+ },
+ )
+
+ return PermissionCheckResult(
+ allowed=False, username=username, role=role, reason=reason
+ )
+
+ async def check_org_membership(self, username: str) -> bool:
+ """
+ Check if user is a member of the repository's organization.
+
+ Args:
+ username: GitHub username
+
+ Returns:
+ True if user is an org member (or repo is not owned by org)
+ """
+ try:
+ # Check if repo is owned by an org
+ repo_info = await self.gh_client.api_get(f"/repos/{self.repo}")
+ if repo_info.get("owner", {}).get("type") != "Organization":
+ logger.debug(f"Repository {self.repo} is not owned by an organization")
+ return True # Not an org repo, so membership check N/A
+
+ # Check org membership
+ try:
+ await self.gh_client.api_get(f"/orgs/{self.owner}/members/{username}")
+ logger.info(f"✓ User {username} is a member of org {self.owner}")
+ return True
+ except Exception:
+ logger.info(f"✗ User {username} is not a member of org {self.owner}")
+ return False
+
+ except Exception as e:
+ logger.error(f"Error checking org membership for {username}: {e}")
+ return False
+
+ async def check_team_membership(self, username: str, team_slug: str) -> bool:
+ """
+ Check if user is a member of a specific team.
+
+ Args:
+ username: GitHub username
+ team_slug: Team slug (e.g., "developers")
+
+ Returns:
+ True if user is a team member
+ """
+ try:
+ await self.gh_client.api_get(
+ f"/orgs/{self.owner}/teams/{team_slug}/memberships/{username}"
+ )
+ logger.info(
+ f"✓ User {username} is a member of team {self.owner}/{team_slug}"
+ )
+ return True
+ except Exception:
+ logger.info(
+ f"✗ User {username} is not a member of team {self.owner}/{team_slug}"
+ )
+ return False
+
+ def log_permission_denial(
+ self,
+ action: str,
+ username: str,
+ role: GitHubRole,
+ issue_number: int | None = None,
+ pr_number: int | None = None,
+ ) -> None:
+ """
+ Log a permission denial with full context.
+
+ Args:
+ action: Action that was denied (e.g., "auto-fix", "pr-review")
+ username: GitHub username
+ role: User's role
+ issue_number: Optional issue number
+ pr_number: Optional PR number
+ """
+ context = {
+ "action": action,
+ "username": username,
+ "role": role,
+ "repo": self.repo,
+ "allowed_roles": self.allowed_roles,
+ "allow_external_contributors": self.allow_external_contributors,
+ }
+
+ if issue_number:
+ context["issue_number"] = issue_number
+ if pr_number:
+ context["pr_number"] = pr_number
+
+ logger.warning(
+ f"PERMISSION DENIED: {username} ({role}) attempted {action} in {self.repo}",
+ extra=context,
+ )
+
+ async def verify_automation_trigger(
+ self, issue_number: int, trigger_label: str
+ ) -> PermissionCheckResult:
+ """
+ Complete verification for an automation trigger (e.g., auto-fix label).
+
+ This is the main entry point for permission checks.
+
+ Args:
+ issue_number: Issue number
+ trigger_label: Label that triggered automation
+
+ Returns:
+ PermissionCheckResult with full details
+
+ Raises:
+ PermissionError: If verification fails
+ """
+ logger.info(
+ f"Verifying automation trigger for issue #{issue_number}, label: {trigger_label}"
+ )
+
+ # Step 1: Find who added the label
+ username, role = await self.check_label_adder(issue_number, trigger_label)
+
+ # Step 2: Check if they're allowed
+ result = await self.is_allowed_for_autofix(username)
+
+ # Step 3: Log if denied
+ if not result.allowed:
+ self.log_permission_denial(
+ action="auto-fix",
+ username=username,
+ role=role,
+ issue_number=issue_number,
+ )
+
+ return result
diff --git a/apps/backend/runners/github/providers/__init__.py b/apps/backend/runners/github/providers/__init__.py
new file mode 100644
index 00000000..52db9fc3
--- /dev/null
+++ b/apps/backend/runners/github/providers/__init__.py
@@ -0,0 +1,48 @@
+"""
+Git Provider Abstraction
+========================
+
+Abstracts git hosting providers (GitHub, GitLab, Bitbucket) behind a common interface.
+
+Usage:
+ from providers import GitProvider, get_provider
+
+ # Get provider based on config
+ provider = get_provider(config)
+
+ # Fetch PR data
+ pr = await provider.fetch_pr(123)
+
+ # Post review
+ await provider.post_review(123, review)
+"""
+
+from .factory import get_provider, register_provider
+from .github_provider import GitHubProvider
+from .protocol import (
+ GitProvider,
+ IssueData,
+ IssueFilters,
+ PRData,
+ PRFilters,
+ ProviderType,
+ ReviewData,
+ ReviewFinding,
+)
+
+__all__ = [
+ # Protocol
+ "GitProvider",
+ "PRData",
+ "IssueData",
+ "ReviewData",
+ "ReviewFinding",
+ "IssueFilters",
+ "PRFilters",
+ "ProviderType",
+ # Implementations
+ "GitHubProvider",
+ # Factory
+ "get_provider",
+ "register_provider",
+]
diff --git a/apps/backend/runners/github/providers/factory.py b/apps/backend/runners/github/providers/factory.py
new file mode 100644
index 00000000..221244a8
--- /dev/null
+++ b/apps/backend/runners/github/providers/factory.py
@@ -0,0 +1,152 @@
+"""
+Provider Factory
+================
+
+Factory functions for creating git provider instances.
+Supports dynamic provider registration for extensibility.
+"""
+
+from __future__ import annotations
+
+from collections.abc import Callable
+from typing import Any
+
+from .github_provider import GitHubProvider
+from .protocol import GitProvider, ProviderType
+
+# Provider registry for dynamic registration
+_PROVIDER_REGISTRY: dict[ProviderType, Callable[..., GitProvider]] = {}
+
+
+def register_provider(
+ provider_type: ProviderType,
+ factory: Callable[..., GitProvider],
+) -> None:
+ """
+ Register a provider factory.
+
+ Args:
+ provider_type: The provider type to register
+ factory: Factory function that creates provider instances
+
+ Example:
+ def create_gitlab(repo: str, **kwargs) -> GitLabProvider:
+ return GitLabProvider(repo=repo, **kwargs)
+
+ register_provider(ProviderType.GITLAB, create_gitlab)
+ """
+ _PROVIDER_REGISTRY[provider_type] = factory
+
+
+def get_provider(
+ provider_type: ProviderType | str,
+ repo: str,
+ **kwargs: Any,
+) -> GitProvider:
+ """
+ Get a provider instance by type.
+
+ Args:
+ provider_type: The provider type (github, gitlab, etc.)
+ repo: Repository in owner/repo format
+ **kwargs: Additional provider-specific arguments
+
+ Returns:
+ GitProvider instance
+
+ Raises:
+ ValueError: If provider type is not supported
+
+ Example:
+ provider = get_provider("github", "owner/repo")
+ pr = await provider.fetch_pr(123)
+ """
+ # Convert string to enum if needed
+ if isinstance(provider_type, str):
+ try:
+ provider_type = ProviderType(provider_type.lower())
+ except ValueError:
+ raise ValueError(
+ f"Unknown provider type: {provider_type}. "
+ f"Supported: {[p.value for p in ProviderType]}"
+ )
+
+ # Check registry first
+ if provider_type in _PROVIDER_REGISTRY:
+ return _PROVIDER_REGISTRY[provider_type](repo=repo, **kwargs)
+
+ # Built-in providers
+ if provider_type == ProviderType.GITHUB:
+ return GitHubProvider(_repo=repo, **kwargs)
+
+ # Future providers (not yet implemented)
+ if provider_type == ProviderType.GITLAB:
+ raise NotImplementedError(
+ "GitLab provider not yet implemented. "
+ "See providers/gitlab_provider.py.stub for interface."
+ )
+
+ if provider_type == ProviderType.BITBUCKET:
+ raise NotImplementedError(
+ "Bitbucket provider not yet implemented. "
+ "See providers/bitbucket_provider.py.stub for interface."
+ )
+
+ if provider_type == ProviderType.GITEA:
+ raise NotImplementedError(
+ "Gitea provider not yet implemented. "
+ "See providers/gitea_provider.py.stub for interface."
+ )
+
+ if provider_type == ProviderType.AZURE_DEVOPS:
+ raise NotImplementedError(
+ "Azure DevOps provider not yet implemented. "
+ "See providers/azure_devops_provider.py.stub for interface."
+ )
+
+ raise ValueError(f"Unsupported provider type: {provider_type}")
+
+
+def list_available_providers() -> list[ProviderType]:
+ """
+ List all available provider types.
+
+ Returns:
+ List of available ProviderType values
+ """
+ available = [ProviderType.GITHUB] # Built-in
+
+ # Add registered providers
+ for provider_type in _PROVIDER_REGISTRY:
+ if provider_type not in available:
+ available.append(provider_type)
+
+ return available
+
+
+def is_provider_available(provider_type: ProviderType | str) -> bool:
+ """
+ Check if a provider is available.
+
+ Args:
+ provider_type: The provider type to check
+
+ Returns:
+ True if the provider is available
+ """
+ if isinstance(provider_type, str):
+ try:
+ provider_type = ProviderType(provider_type.lower())
+ except ValueError:
+ return False
+
+ # GitHub is always available
+ if provider_type == ProviderType.GITHUB:
+ return True
+
+ # Check registry
+ return provider_type in _PROVIDER_REGISTRY
+
+
+# Register default providers
+# (Future implementations can be registered here or by external packages)
diff --git a/apps/backend/runners/github/providers/github_provider.py b/apps/backend/runners/github/providers/github_provider.py
new file mode 100644
index 00000000..558d0fb2
--- /dev/null
+++ b/apps/backend/runners/github/providers/github_provider.py
@@ -0,0 +1,531 @@
+"""
+GitHub Provider Implementation
+==============================
+
+Implements the GitProvider protocol for GitHub using the gh CLI.
+Wraps the existing GHClient functionality.
+"""
+
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass
+from datetime import datetime, timezone
+from typing import Any
+
+# Import from parent package or direct import
+try:
+ from ..gh_client import GHClient
+except (ImportError, ValueError, SystemError):
+ from gh_client import GHClient
+
+from .protocol import (
+ IssueData,
+ IssueFilters,
+ LabelData,
+ PRData,
+ PRFilters,
+ ProviderType,
+ ReviewData,
+)
+
+
+@dataclass
+class GitHubProvider:
+ """
+ GitHub implementation of the GitProvider protocol.
+
+ Uses the gh CLI for all operations.
+
+ Usage:
+ provider = GitHubProvider(repo="owner/repo")
+ pr = await provider.fetch_pr(123)
+ await provider.post_review(123, review)
+ """
+
+ _repo: str
+ _gh_client: GHClient | None = None
+ _project_dir: str | None = None
+ enable_rate_limiting: bool = True
+
+ def __post_init__(self):
+ if self._gh_client is None:
+ from pathlib import Path
+
+ project_dir = Path(self._project_dir) if self._project_dir else Path.cwd()
+ self._gh_client = GHClient(
+ project_dir=project_dir,
+ enable_rate_limiting=self.enable_rate_limiting,
+ )
+
+ @property
+ def provider_type(self) -> ProviderType:
+ return ProviderType.GITHUB
+
+ @property
+ def repo(self) -> str:
+ return self._repo
+
+ @property
+ def gh_client(self) -> GHClient:
+ """Get the underlying GHClient."""
+ return self._gh_client
+
+ # -------------------------------------------------------------------------
+ # Pull Request Operations
+ # -------------------------------------------------------------------------
+
+ async def fetch_pr(self, number: int) -> PRData:
+ """Fetch a pull request by number."""
+ fields = [
+ "number",
+ "title",
+ "body",
+ "author",
+ "state",
+ "headRefName",
+ "baseRefName",
+ "additions",
+ "deletions",
+ "changedFiles",
+ "files",
+ "url",
+ "createdAt",
+ "updatedAt",
+ "labels",
+ "reviewRequests",
+ "isDraft",
+ "mergeable",
+ ]
+
+ pr_data = await self._gh_client.pr_get(number, json_fields=fields)
+ diff = await self._gh_client.pr_diff(number)
+
+ return self._parse_pr_data(pr_data, diff)
+
+ async def fetch_prs(self, filters: PRFilters | None = None) -> list[PRData]:
+ """Fetch pull requests with optional filters."""
+ filters = filters or PRFilters()
+
+ prs = await self._gh_client.pr_list(
+ state=filters.state,
+ limit=filters.limit,
+ json_fields=[
+ "number",
+ "title",
+ "author",
+ "state",
+ "headRefName",
+ "baseRefName",
+ "labels",
+ "url",
+ "createdAt",
+ "updatedAt",
+ ],
+ )
+
+ result = []
+ for pr_data in prs:
+ # Apply additional filters
+ if (
+ filters.author
+ and pr_data.get("author", {}).get("login") != filters.author
+ ):
+ continue
+ if (
+ filters.base_branch
+ and pr_data.get("baseRefName") != filters.base_branch
+ ):
+ continue
+ if (
+ filters.head_branch
+ and pr_data.get("headRefName") != filters.head_branch
+ ):
+ continue
+ if filters.labels:
+ pr_labels = [label.get("name") for label in pr_data.get("labels", [])]
+ if not all(label in pr_labels for label in filters.labels):
+ continue
+
+ # Parse to PRData (lightweight, no diff)
+ result.append(self._parse_pr_data(pr_data, ""))
+
+ return result
+
+ async def fetch_pr_diff(self, number: int) -> str:
+ """Fetch the diff for a pull request."""
+ return await self._gh_client.pr_diff(number)
+
+ async def post_review(self, pr_number: int, review: ReviewData) -> int:
+ """Post a review to a pull request."""
+ return await self._gh_client.pr_review(
+ pr_number=pr_number,
+ body=review.body,
+ event=review.event.upper(),
+ )
+
+ async def merge_pr(
+ self,
+ pr_number: int,
+ merge_method: str = "merge",
+ commit_title: str | None = None,
+ ) -> bool:
+ """Merge a pull request."""
+ cmd = ["pr", "merge", str(pr_number)]
+
+ if merge_method == "squash":
+ cmd.append("--squash")
+ elif merge_method == "rebase":
+ cmd.append("--rebase")
+ else:
+ cmd.append("--merge")
+
+ if commit_title:
+ cmd.extend(["--subject", commit_title])
+
+ cmd.append("--yes")
+
+ try:
+ await self._gh_client._run_gh_command(cmd)
+ return True
+ except Exception:
+ return False
+
+ async def close_pr(
+ self,
+ pr_number: int,
+ comment: str | None = None,
+ ) -> bool:
+ """Close a pull request without merging."""
+ try:
+ if comment:
+ await self.add_comment(pr_number, comment)
+ await self._gh_client._run_gh_command(["pr", "close", str(pr_number)])
+ return True
+ except Exception:
+ return False
+
+ # -------------------------------------------------------------------------
+ # Issue Operations
+ # -------------------------------------------------------------------------
+
+ async def fetch_issue(self, number: int) -> IssueData:
+ """Fetch an issue by number."""
+ fields = [
+ "number",
+ "title",
+ "body",
+ "author",
+ "state",
+ "labels",
+ "createdAt",
+ "updatedAt",
+ "url",
+ "assignees",
+ "milestone",
+ ]
+
+ issue_data = await self._gh_client.issue_get(number, json_fields=fields)
+ return self._parse_issue_data(issue_data)
+
+ async def fetch_issues(
+ self, filters: IssueFilters | None = None
+ ) -> list[IssueData]:
+ """Fetch issues with optional filters."""
+ filters = filters or IssueFilters()
+
+ issues = await self._gh_client.issue_list(
+ state=filters.state,
+ limit=filters.limit,
+ json_fields=[
+ "number",
+ "title",
+ "body",
+ "author",
+ "state",
+ "labels",
+ "createdAt",
+ "updatedAt",
+ "url",
+ "assignees",
+ "milestone",
+ ],
+ )
+
+ result = []
+ for issue_data in issues:
+ # Filter out PRs if requested
+ if not filters.include_prs and "pullRequest" in issue_data:
+ continue
+
+ # Apply filters
+ if (
+ filters.author
+ and issue_data.get("author", {}).get("login") != filters.author
+ ):
+ continue
+ if filters.labels:
+ issue_labels = [
+ label.get("name") for label in issue_data.get("labels", [])
+ ]
+ if not all(label in issue_labels for label in filters.labels):
+ continue
+
+ result.append(self._parse_issue_data(issue_data))
+
+ return result
+
+ async def create_issue(
+ self,
+ title: str,
+ body: str,
+ labels: list[str] | None = None,
+ assignees: list[str] | None = None,
+ ) -> IssueData:
+ """Create a new issue."""
+ cmd = ["issue", "create", "--title", title, "--body", body]
+
+ if labels:
+ for label in labels:
+ cmd.extend(["--label", label])
+
+ if assignees:
+ for assignee in assignees:
+ cmd.extend(["--assignee", assignee])
+
+ result = await self._gh_client._run_gh_command(cmd)
+
+ # Parse the issue URL to get the number
+ # gh issue create outputs the URL
+ url = result.strip()
+ number = int(url.split("/")[-1])
+
+ return await self.fetch_issue(number)
+
+ async def close_issue(
+ self,
+ number: int,
+ comment: str | None = None,
+ ) -> bool:
+ """Close an issue."""
+ try:
+ if comment:
+ await self.add_comment(number, comment)
+ await self._gh_client._run_gh_command(["issue", "close", str(number)])
+ return True
+ except Exception:
+ return False
+
+ async def add_comment(
+ self,
+ issue_or_pr_number: int,
+ body: str,
+ ) -> int:
+ """Add a comment to an issue or PR."""
+ await self._gh_client.issue_comment(issue_or_pr_number, body)
+ # gh CLI doesn't return comment ID, return 0
+ return 0
+
+ # -------------------------------------------------------------------------
+ # Label Operations
+ # -------------------------------------------------------------------------
+
+ async def apply_labels(
+ self,
+ issue_or_pr_number: int,
+ labels: list[str],
+ ) -> None:
+ """Apply labels to an issue or PR."""
+ await self._gh_client.issue_add_labels(issue_or_pr_number, labels)
+
+ async def remove_labels(
+ self,
+ issue_or_pr_number: int,
+ labels: list[str],
+ ) -> None:
+ """Remove labels from an issue or PR."""
+ await self._gh_client.issue_remove_labels(issue_or_pr_number, labels)
+
+ async def create_label(self, label: LabelData) -> None:
+ """Create a label in the repository."""
+ cmd = ["label", "create", label.name, "--color", label.color]
+ if label.description:
+ cmd.extend(["--description", label.description])
+ cmd.append("--force") # Update if exists
+
+ await self._gh_client._run_gh_command(cmd)
+
+ async def list_labels(self) -> list[LabelData]:
+ """List all labels in the repository."""
+ result = await self._gh_client._run_gh_command(
+ [
+ "label",
+ "list",
+ "--json",
+ "name,color,description",
+ ]
+ )
+
+ labels_data = json.loads(result) if result else []
+ return [
+ LabelData(
+ name=label["name"],
+ color=label.get("color", ""),
+ description=label.get("description", ""),
+ )
+ for label in labels_data
+ ]
+
+ # -------------------------------------------------------------------------
+ # Repository Operations
+ # -------------------------------------------------------------------------
+
+ async def get_repository_info(self) -> dict[str, Any]:
+ """Get repository information."""
+ return await self._gh_client.api_get(f"/repos/{self._repo}")
+
+ async def get_default_branch(self) -> str:
+ """Get the default branch name."""
+ repo_info = await self.get_repository_info()
+ return repo_info.get("default_branch", "main")
+
+ async def check_permissions(self, username: str) -> str:
+ """Check a user's permission level on the repository."""
+ try:
+ result = await self._gh_client.api_get(
+ f"/repos/{self._repo}/collaborators/{username}/permission"
+ )
+ return result.get("permission", "none")
+ except Exception:
+ return "none"
+
+ # -------------------------------------------------------------------------
+ # API Operations
+ # -------------------------------------------------------------------------
+
+ async def api_get(
+ self,
+ endpoint: str,
+ params: dict[str, Any] | None = None,
+ ) -> Any:
+ """Make a GET request to the GitHub API."""
+ return await self._gh_client.api_get(endpoint, params)
+
+ async def api_post(
+ self,
+ endpoint: str,
+ data: dict[str, Any] | None = None,
+ ) -> Any:
+ """Make a POST request to the GitHub API."""
+ return await self._gh_client.api_post(endpoint, data)
+
+ # -------------------------------------------------------------------------
+ # Helper Methods
+ # -------------------------------------------------------------------------
+
+ def _parse_pr_data(self, data: dict[str, Any], diff: str) -> PRData:
+ """Parse GitHub PR data into PRData."""
+ author = data.get("author", {})
+ if isinstance(author, dict):
+ author_login = author.get("login", "unknown")
+ else:
+ author_login = str(author) if author else "unknown"
+
+ labels = []
+ for label in data.get("labels", []):
+ if isinstance(label, dict):
+ labels.append(label.get("name", ""))
+ else:
+ labels.append(str(label))
+
+ files = data.get("files", [])
+ if files is None:
+ files = []
+
+ return PRData(
+ number=data.get("number", 0),
+ title=data.get("title", ""),
+ body=data.get("body", "") or "",
+ author=author_login,
+ state=data.get("state", "open"),
+ source_branch=data.get("headRefName", ""),
+ target_branch=data.get("baseRefName", ""),
+ additions=data.get("additions", 0),
+ deletions=data.get("deletions", 0),
+ changed_files=data.get("changedFiles", len(files)),
+ files=files,
+ diff=diff,
+ url=data.get("url", ""),
+ created_at=self._parse_datetime(data.get("createdAt")),
+ updated_at=self._parse_datetime(data.get("updatedAt")),
+ labels=labels,
+ reviewers=self._parse_reviewers(data.get("reviewRequests", [])),
+ is_draft=data.get("isDraft", False),
+ mergeable=data.get("mergeable") != "CONFLICTING",
+ provider=ProviderType.GITHUB,
+ raw_data=data,
+ )
+
+ def _parse_issue_data(self, data: dict[str, Any]) -> IssueData:
+ """Parse GitHub issue data into IssueData."""
+ author = data.get("author", {})
+ if isinstance(author, dict):
+ author_login = author.get("login", "unknown")
+ else:
+ author_login = str(author) if author else "unknown"
+
+ labels = []
+ for label in data.get("labels", []):
+ if isinstance(label, dict):
+ labels.append(label.get("name", ""))
+ else:
+ labels.append(str(label))
+
+ assignees = []
+ for assignee in data.get("assignees", []):
+ if isinstance(assignee, dict):
+ assignees.append(assignee.get("login", ""))
+ else:
+ assignees.append(str(assignee))
+
+ milestone = data.get("milestone")
+ if isinstance(milestone, dict):
+ milestone = milestone.get("title")
+
+ return IssueData(
+ number=data.get("number", 0),
+ title=data.get("title", ""),
+ body=data.get("body", "") or "",
+ author=author_login,
+ state=data.get("state", "open"),
+ labels=labels,
+ created_at=self._parse_datetime(data.get("createdAt")),
+ updated_at=self._parse_datetime(data.get("updatedAt")),
+ url=data.get("url", ""),
+ assignees=assignees,
+ milestone=milestone,
+ provider=ProviderType.GITHUB,
+ raw_data=data,
+ )
+
+ def _parse_datetime(self, dt_str: str | None) -> datetime:
+ """Parse ISO datetime string."""
+ if not dt_str:
+ return datetime.now(timezone.utc)
+ try:
+ return datetime.fromisoformat(dt_str.replace("Z", "+00:00"))
+ except (ValueError, AttributeError):
+ return datetime.now(timezone.utc)
+
+ def _parse_reviewers(self, review_requests: list | None) -> list[str]:
+ """Parse review requests into list of usernames."""
+ if not review_requests:
+ return []
+ reviewers = []
+ for req in review_requests:
+ if isinstance(req, dict):
+ if "requestedReviewer" in req:
+ reviewer = req["requestedReviewer"]
+ if isinstance(reviewer, dict):
+ reviewers.append(reviewer.get("login", ""))
+ return reviewers
diff --git a/apps/backend/runners/github/providers/protocol.py b/apps/backend/runners/github/providers/protocol.py
new file mode 100644
index 00000000..de67e0cd
--- /dev/null
+++ b/apps/backend/runners/github/providers/protocol.py
@@ -0,0 +1,491 @@
+"""
+Git Provider Protocol
+=====================
+
+Defines the abstract interface that all git hosting providers must implement.
+Enables support for GitHub, GitLab, Bitbucket, and other providers.
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from datetime import datetime
+from enum import Enum
+from typing import Any, Protocol, runtime_checkable
+
+
+class ProviderType(str, Enum):
+ """Supported git hosting providers."""
+
+ GITHUB = "github"
+ GITLAB = "gitlab"
+ BITBUCKET = "bitbucket"
+ GITEA = "gitea"
+ AZURE_DEVOPS = "azure_devops"
+
+
+# ============================================================================
+# DATA MODELS
+# ============================================================================
+
+
+@dataclass
+class PRData:
+ """
+ Pull/Merge Request data structure.
+
+ Provider-agnostic representation of a pull request.
+ """
+
+ number: int
+ title: str
+ body: str
+ author: str
+ state: str # open, closed, merged
+ source_branch: str
+ target_branch: str
+ additions: int
+ deletions: int
+ changed_files: int
+ files: list[dict[str, Any]]
+ diff: str
+ url: str
+ created_at: datetime
+ updated_at: datetime
+ labels: list[str] = field(default_factory=list)
+ reviewers: list[str] = field(default_factory=list)
+ is_draft: bool = False
+ mergeable: bool = True
+ provider: ProviderType = ProviderType.GITHUB
+
+ # Provider-specific raw data (for debugging)
+ raw_data: dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass
+class IssueData:
+ """
+ Issue/Ticket data structure.
+
+ Provider-agnostic representation of an issue.
+ """
+
+ number: int
+ title: str
+ body: str
+ author: str
+ state: str # open, closed
+ labels: list[str]
+ created_at: datetime
+ updated_at: datetime
+ url: str
+ assignees: list[str] = field(default_factory=list)
+ milestone: str | None = None
+ provider: ProviderType = ProviderType.GITHUB
+
+ # Provider-specific raw data
+ raw_data: dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass
+class ReviewFinding:
+ """
+ Individual finding in a code review.
+ """
+
+ id: str
+ severity: str # critical, high, medium, low, info
+ category: str # security, bug, performance, style, etc.
+ title: str
+ description: str
+ file: str | None = None
+ line: int | None = None
+ end_line: int | None = None
+ suggested_fix: str | None = None
+ confidence: float = 0.8 # P3-4: Confidence scoring
+ evidence: list[str] = field(default_factory=list)
+ fixable: bool = False
+
+
+@dataclass
+class ReviewData:
+ """
+ Code review data structure.
+
+ Provider-agnostic representation of a review.
+ """
+
+ pr_number: int
+ event: str # approve, request_changes, comment
+ body: str
+ findings: list[ReviewFinding] = field(default_factory=list)
+ inline_comments: list[dict[str, Any]] = field(default_factory=list)
+
+
+@dataclass
+class IssueFilters:
+ """
+ Filters for listing issues.
+ """
+
+ state: str = "open"
+ labels: list[str] = field(default_factory=list)
+ author: str | None = None
+ assignee: str | None = None
+ since: datetime | None = None
+ limit: int = 100
+ include_prs: bool = False
+
+
+@dataclass
+class PRFilters:
+ """
+ Filters for listing pull requests.
+ """
+
+ state: str = "open"
+ labels: list[str] = field(default_factory=list)
+ author: str | None = None
+ base_branch: str | None = None
+ head_branch: str | None = None
+ since: datetime | None = None
+ limit: int = 100
+
+
+@dataclass
+class LabelData:
+ """
+ Label data structure.
+ """
+
+ name: str
+ color: str
+ description: str = ""
+
+
+# ============================================================================
+# PROVIDER PROTOCOL
+# ============================================================================
+
+
+@runtime_checkable
+class GitProvider(Protocol):
+ """
+ Abstract protocol for git hosting providers.
+
+ All provider implementations must implement these methods.
+ This enables the system to work with GitHub, GitLab, Bitbucket, etc.
+ """
+
+ @property
+ def provider_type(self) -> ProviderType:
+ """Get the provider type."""
+ ...
+
+ @property
+ def repo(self) -> str:
+ """Get the repository in owner/repo format."""
+ ...
+
+ # -------------------------------------------------------------------------
+ # Pull Request Operations
+ # -------------------------------------------------------------------------
+
+ async def fetch_pr(self, number: int) -> PRData:
+ """
+ Fetch a pull request by number.
+
+ Args:
+ number: PR/MR number
+
+ Returns:
+ PRData with full PR details including diff
+ """
+ ...
+
+ async def fetch_prs(self, filters: PRFilters | None = None) -> list[PRData]:
+ """
+ Fetch pull requests with optional filters.
+
+ Args:
+ filters: Optional filters (state, labels, etc.)
+
+ Returns:
+ List of PRData
+ """
+ ...
+
+ async def fetch_pr_diff(self, number: int) -> str:
+ """
+ Fetch the diff for a pull request.
+
+ Args:
+ number: PR number
+
+ Returns:
+ Unified diff string
+ """
+ ...
+
+ async def post_review(
+ self,
+ pr_number: int,
+ review: ReviewData,
+ ) -> int:
+ """
+ Post a review to a pull request.
+
+ Args:
+ pr_number: PR number
+ review: Review data with findings and comments
+
+ Returns:
+ Review ID
+ """
+ ...
+
+ async def merge_pr(
+ self,
+ pr_number: int,
+ merge_method: str = "merge",
+ commit_title: str | None = None,
+ ) -> bool:
+ """
+ Merge a pull request.
+
+ Args:
+ pr_number: PR number
+ merge_method: merge, squash, or rebase
+ commit_title: Optional commit title
+
+ Returns:
+ True if merged successfully
+ """
+ ...
+
+ async def close_pr(
+ self,
+ pr_number: int,
+ comment: str | None = None,
+ ) -> bool:
+ """
+ Close a pull request without merging.
+
+ Args:
+ pr_number: PR number
+ comment: Optional closing comment
+
+ Returns:
+ True if closed successfully
+ """
+ ...
+
+ # -------------------------------------------------------------------------
+ # Issue Operations
+ # -------------------------------------------------------------------------
+
+ async def fetch_issue(self, number: int) -> IssueData:
+ """
+ Fetch an issue by number.
+
+ Args:
+ number: Issue number
+
+ Returns:
+ IssueData with full issue details
+ """
+ ...
+
+ async def fetch_issues(
+ self, filters: IssueFilters | None = None
+ ) -> list[IssueData]:
+ """
+ Fetch issues with optional filters.
+
+ Args:
+ filters: Optional filters
+
+ Returns:
+ List of IssueData
+ """
+ ...
+
+ async def create_issue(
+ self,
+ title: str,
+ body: str,
+ labels: list[str] | None = None,
+ assignees: list[str] | None = None,
+ ) -> IssueData:
+ """
+ Create a new issue.
+
+ Args:
+ title: Issue title
+ body: Issue body
+ labels: Optional labels
+ assignees: Optional assignees
+
+ Returns:
+ Created IssueData
+ """
+ ...
+
+ async def close_issue(
+ self,
+ number: int,
+ comment: str | None = None,
+ ) -> bool:
+ """
+ Close an issue.
+
+ Args:
+ number: Issue number
+ comment: Optional closing comment
+
+ Returns:
+ True if closed successfully
+ """
+ ...
+
+ async def add_comment(
+ self,
+ issue_or_pr_number: int,
+ body: str,
+ ) -> int:
+ """
+ Add a comment to an issue or PR.
+
+ Args:
+ issue_or_pr_number: Issue/PR number
+ body: Comment body
+
+ Returns:
+ Comment ID
+ """
+ ...
+
+ # -------------------------------------------------------------------------
+ # Label Operations
+ # -------------------------------------------------------------------------
+
+ async def apply_labels(
+ self,
+ issue_or_pr_number: int,
+ labels: list[str],
+ ) -> None:
+ """
+ Apply labels to an issue or PR.
+
+ Args:
+ issue_or_pr_number: Issue/PR number
+ labels: Labels to apply
+ """
+ ...
+
+ async def remove_labels(
+ self,
+ issue_or_pr_number: int,
+ labels: list[str],
+ ) -> None:
+ """
+ Remove labels from an issue or PR.
+
+ Args:
+ issue_or_pr_number: Issue/PR number
+ labels: Labels to remove
+ """
+ ...
+
+ async def create_label(
+ self,
+ label: LabelData,
+ ) -> None:
+ """
+ Create a label in the repository.
+
+ Args:
+ label: Label data
+ """
+ ...
+
+ async def list_labels(self) -> list[LabelData]:
+ """
+ List all labels in the repository.
+
+ Returns:
+ List of LabelData
+ """
+ ...
+
+ # -------------------------------------------------------------------------
+ # Repository Operations
+ # -------------------------------------------------------------------------
+
+ async def get_repository_info(self) -> dict[str, Any]:
+ """
+ Get repository information.
+
+ Returns:
+ Repository metadata
+ """
+ ...
+
+ async def get_default_branch(self) -> str:
+ """
+ Get the default branch name.
+
+ Returns:
+ Default branch name (e.g., "main", "master")
+ """
+ ...
+
+ async def check_permissions(self, username: str) -> str:
+ """
+ Check a user's permission level on the repository.
+
+ Args:
+ username: GitHub/GitLab username
+
+ Returns:
+ Permission level (admin, write, read, none)
+ """
+ ...
+
+ # -------------------------------------------------------------------------
+ # API Operations (Low-level)
+ # -------------------------------------------------------------------------
+
+ async def api_get(
+ self,
+ endpoint: str,
+ params: dict[str, Any] | None = None,
+ ) -> Any:
+ """
+ Make a GET request to the provider API.
+
+ Args:
+ endpoint: API endpoint
+ params: Query parameters
+
+ Returns:
+ API response data
+ """
+ ...
+
+ async def api_post(
+ self,
+ endpoint: str,
+ data: dict[str, Any] | None = None,
+ ) -> Any:
+ """
+ Make a POST request to the provider API.
+
+ Args:
+ endpoint: API endpoint
+ data: Request body
+
+ Returns:
+ API response data
+ """
+ ...
diff --git a/apps/backend/runners/github/purge_strategy.py b/apps/backend/runners/github/purge_strategy.py
new file mode 100644
index 00000000..d9c20a01
--- /dev/null
+++ b/apps/backend/runners/github/purge_strategy.py
@@ -0,0 +1,288 @@
+"""
+Purge Strategy
+==============
+
+Generic GDPR-compliant data purge implementation for GitHub automation system.
+
+Features:
+- Generic purge method for issues, PRs, and repositories
+- Pattern-based file discovery
+- Optional repository filtering
+- Archive directory cleanup
+- Comprehensive error handling
+
+Usage:
+ strategy = PurgeStrategy(state_dir=Path(".auto-claude/github"))
+ result = await strategy.purge_by_criteria(
+ pattern="issue",
+ key="issue_number",
+ value=123
+ )
+"""
+
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+
+
+@dataclass
+class PurgeResult:
+ """
+ Result of a purge operation.
+ """
+
+ deleted_count: int = 0
+ freed_bytes: int = 0
+ errors: list[str] = field(default_factory=list)
+ started_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
+ completed_at: datetime | None = None
+
+ @property
+ def freed_mb(self) -> float:
+ return self.freed_bytes / (1024 * 1024)
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "deleted_count": self.deleted_count,
+ "freed_bytes": self.freed_bytes,
+ "freed_mb": round(self.freed_mb, 2),
+ "errors": self.errors,
+ "started_at": self.started_at.isoformat(),
+ "completed_at": self.completed_at.isoformat()
+ if self.completed_at
+ else None,
+ }
+
+
+class PurgeStrategy:
+ """
+ Generic purge strategy for GDPR-compliant data deletion.
+
+ Consolidates purge_issue(), purge_pr(), and purge_repo() into a single
+ flexible implementation that works for all entity types.
+
+ Usage:
+ strategy = PurgeStrategy(state_dir)
+
+ # Purge issue
+ await strategy.purge_by_criteria(
+ pattern="issue",
+ key="issue_number",
+ value=123,
+ repo="owner/repo" # optional
+ )
+
+ # Purge PR
+ await strategy.purge_by_criteria(
+ pattern="pr",
+ key="pr_number",
+ value=456
+ )
+
+ # Purge repo (uses different logic)
+ await strategy.purge_repository("owner/repo")
+ """
+
+ def __init__(self, state_dir: Path):
+ """
+ Initialize purge strategy.
+
+ Args:
+ state_dir: Base directory containing GitHub automation data
+ """
+ self.state_dir = state_dir
+ self.archive_dir = state_dir / "archive"
+
+ async def purge_by_criteria(
+ self,
+ pattern: str,
+ key: str,
+ value: Any,
+ repo: str | None = None,
+ ) -> PurgeResult:
+ """
+ Purge all data matching specified criteria (GDPR-compliant).
+
+ This generic method eliminates duplicate purge_issue() and purge_pr()
+ implementations by using pattern-based file discovery and JSON
+ key matching.
+
+ Args:
+ pattern: File pattern identifier (e.g., "issue", "pr")
+ key: JSON key to match (e.g., "issue_number", "pr_number")
+ value: Value to match (e.g., 123, 456)
+ repo: Optional repository filter in "owner/repo" format
+
+ Returns:
+ PurgeResult with deletion statistics
+
+ Example:
+ # Purge issue #123
+ result = await strategy.purge_by_criteria(
+ pattern="issue",
+ key="issue_number",
+ value=123
+ )
+
+ # Purge PR #456 from specific repo
+ result = await strategy.purge_by_criteria(
+ pattern="pr",
+ key="pr_number",
+ value=456,
+ repo="owner/repo"
+ )
+ """
+ result = PurgeResult()
+
+ # Build file patterns to search for
+ patterns = [
+ f"*{value}*.json",
+ f"*{pattern}-{value}*.json",
+ f"*_{value}_*.json",
+ ]
+
+ # Search state directory
+ for file_pattern in patterns:
+ for file_path in self.state_dir.rglob(file_pattern):
+ self._try_delete_file(file_path, key, value, repo, result)
+
+ # Search archive directory
+ for file_pattern in patterns:
+ for file_path in self.archive_dir.rglob(file_pattern):
+ self._try_delete_file_simple(file_path, result)
+
+ result.completed_at = datetime.now(timezone.utc)
+ return result
+
+ async def purge_repository(self, repo: str) -> PurgeResult:
+ """
+ Purge all data for a specific repository.
+
+ This method handles repository-level purges which have different
+ logic than issue/PR purges (directory-based instead of file-based).
+
+ Args:
+ repo: Repository in "owner/repo" format
+
+ Returns:
+ PurgeResult with deletion statistics
+ """
+ import shutil
+
+ result = PurgeResult()
+ safe_name = repo.replace("/", "_")
+
+ # Delete files matching repository pattern in subdirectories
+ for subdir in ["pr", "issues", "autofix", "trust", "learning"]:
+ dir_path = self.state_dir / subdir
+ if not dir_path.exists():
+ continue
+
+ for file_path in dir_path.glob(f"{safe_name}*.json"):
+ try:
+ file_size = file_path.stat().st_size
+ file_path.unlink()
+ result.deleted_count += 1
+ result.freed_bytes += file_size
+ except OSError as e:
+ result.errors.append(f"Error deleting {file_path}: {e}")
+
+ # Delete entire repository directory
+ repo_dir = self.state_dir / "repos" / safe_name
+ if repo_dir.exists():
+ try:
+ freed = self._calculate_directory_size(repo_dir)
+ shutil.rmtree(repo_dir)
+ result.deleted_count += 1
+ result.freed_bytes += freed
+ except OSError as e:
+ result.errors.append(f"Error deleting repo directory {repo_dir}: {e}")
+
+ result.completed_at = datetime.now(timezone.utc)
+ return result
+
+ def _try_delete_file(
+ self,
+ file_path: Path,
+ key: str,
+ value: Any,
+ repo: str | None,
+ result: PurgeResult,
+ ) -> None:
+ """
+ Attempt to delete a file after validating its JSON contents.
+
+ Args:
+ file_path: Path to file to potentially delete
+ key: JSON key to match
+ value: Value to match
+ repo: Optional repository filter
+ result: PurgeResult to update
+ """
+ try:
+ with open(file_path) as f:
+ data = json.load(f)
+
+ # Verify key matches value
+ if data.get(key) != value:
+ return
+
+ # Apply repository filter if specified
+ if repo and data.get("repo") != repo:
+ return
+
+ # Delete the file
+ file_size = file_path.stat().st_size
+ file_path.unlink()
+ result.deleted_count += 1
+ result.freed_bytes += file_size
+
+ except (OSError, json.JSONDecodeError, KeyError) as e:
+ # Skip files that can't be read or parsed
+ # Don't add to errors as this is expected for non-matching files
+ pass
+ except Exception as e:
+ result.errors.append(f"Unexpected error deleting {file_path}: {e}")
+
+ def _try_delete_file_simple(
+ self,
+ file_path: Path,
+ result: PurgeResult,
+ ) -> None:
+ """
+ Attempt to delete a file without validation (for archive cleanup).
+
+ Args:
+ file_path: Path to file to delete
+ result: PurgeResult to update
+ """
+ try:
+ file_size = file_path.stat().st_size
+ file_path.unlink()
+ result.deleted_count += 1
+ result.freed_bytes += file_size
+ except OSError as e:
+ result.errors.append(f"Error deleting {file_path}: {e}")
+
+ def _calculate_directory_size(self, path: Path) -> int:
+ """
+ Calculate total size of all files in a directory recursively.
+
+ Args:
+ path: Directory path to measure
+
+ Returns:
+ Total size in bytes
+ """
+ total = 0
+ for file_path in path.rglob("*"):
+ if file_path.is_file():
+ try:
+ total += file_path.stat().st_size
+ except OSError:
+ continue
+ return total
diff --git a/apps/backend/runners/github/rate_limiter.py b/apps/backend/runners/github/rate_limiter.py
new file mode 100644
index 00000000..b92d77c8
--- /dev/null
+++ b/apps/backend/runners/github/rate_limiter.py
@@ -0,0 +1,698 @@
+"""
+Rate Limiting Protection for GitHub Automation
+===============================================
+
+Comprehensive rate limiting system that protects against:
+1. GitHub API rate limits (5000 req/hour for authenticated users)
+2. AI API cost overruns (configurable budget per run)
+3. Thundering herd problems (exponential backoff)
+
+Components:
+- TokenBucket: Classic token bucket algorithm for rate limiting
+- RateLimiter: Singleton managing GitHub and AI cost limits
+- @rate_limited decorator: Automatic pre-flight checks with retry logic
+- Cost tracking: Per-model AI API cost calculation and budgeting
+
+Usage:
+ # Singleton instance
+ limiter = RateLimiter.get_instance(
+ github_limit=5000,
+ github_refill_rate=1.4, # tokens per second
+ cost_limit=10.0, # $10 per run
+ )
+
+ # Decorate GitHub operations
+ @rate_limited(operation_type="github")
+ async def fetch_pr_data(pr_number: int):
+ result = subprocess.run(["gh", "pr", "view", str(pr_number)])
+ return result
+
+ # Track AI costs
+ limiter.track_ai_cost(
+ input_tokens=1000,
+ output_tokens=500,
+ model="claude-sonnet-4-20250514"
+ )
+
+ # Manual rate check
+ if not await limiter.acquire_github():
+ raise RateLimitExceeded("GitHub API rate limit reached")
+"""
+
+from __future__ import annotations
+
+import asyncio
+import functools
+import time
+from collections.abc import Callable
+from dataclasses import dataclass, field
+from datetime import datetime, timedelta
+from typing import Any, TypeVar
+
+# Type for decorated functions
+F = TypeVar("F", bound=Callable[..., Any])
+
+
+class RateLimitExceeded(Exception):
+ """Raised when rate limit is exceeded and cannot proceed."""
+
+ pass
+
+
+class CostLimitExceeded(Exception):
+ """Raised when AI cost budget is exceeded."""
+
+ pass
+
+
+@dataclass
+class TokenBucket:
+ """
+ Token bucket algorithm for rate limiting.
+
+ The bucket has a maximum capacity and refills at a constant rate.
+ Each operation consumes one token. If bucket is empty, operations
+ must wait for refill or be rejected.
+
+ Args:
+ capacity: Maximum number of tokens (e.g., 5000 for GitHub)
+ refill_rate: Tokens added per second (e.g., 1.4 for 5000/hour)
+ """
+
+ capacity: int
+ refill_rate: float # tokens per second
+ tokens: float = field(init=False)
+ last_refill: float = field(init=False)
+
+ def __post_init__(self):
+ """Initialize bucket as full."""
+ self.tokens = float(self.capacity)
+ self.last_refill = time.monotonic()
+
+ def _refill(self) -> None:
+ """Refill bucket based on elapsed time."""
+ now = time.monotonic()
+ elapsed = now - self.last_refill
+ tokens_to_add = elapsed * self.refill_rate
+ self.tokens = min(self.capacity, self.tokens + tokens_to_add)
+ self.last_refill = now
+
+ def try_acquire(self, tokens: int = 1) -> bool:
+ """
+ Try to acquire tokens from bucket.
+
+ Returns:
+ True if tokens acquired, False if insufficient tokens
+ """
+ self._refill()
+ if self.tokens >= tokens:
+ self.tokens -= tokens
+ return True
+ return False
+
+ async def acquire(self, tokens: int = 1, timeout: float | None = None) -> bool:
+ """
+ Acquire tokens from bucket, waiting if necessary.
+
+ Args:
+ tokens: Number of tokens to acquire
+ timeout: Maximum time to wait in seconds
+
+ Returns:
+ True if tokens acquired, False if timeout reached
+ """
+ start_time = time.monotonic()
+
+ while True:
+ if self.try_acquire(tokens):
+ return True
+
+ # Check timeout
+ if timeout is not None:
+ elapsed = time.monotonic() - start_time
+ if elapsed >= timeout:
+ return False
+
+ # Wait for next refill
+ # Calculate time until we have enough tokens
+ tokens_needed = tokens - self.tokens
+ wait_time = min(tokens_needed / self.refill_rate, 1.0) # Max 1 second wait
+ await asyncio.sleep(wait_time)
+
+ def available(self) -> int:
+ """Get number of available tokens."""
+ self._refill()
+ return int(self.tokens)
+
+ def time_until_available(self, tokens: int = 1) -> float:
+ """
+ Calculate seconds until requested tokens available.
+
+ Returns:
+ 0 if tokens immediately available, otherwise seconds to wait
+ """
+ self._refill()
+ if self.tokens >= tokens:
+ return 0.0
+ tokens_needed = tokens - self.tokens
+ return tokens_needed / self.refill_rate
+
+
+# AI model pricing (per 1M tokens)
+AI_PRICING = {
+ # Claude models (as of 2025)
+ "claude-sonnet-4-20250514": {"input": 3.00, "output": 15.00},
+ "claude-opus-4-20250514": {"input": 15.00, "output": 75.00},
+ "claude-sonnet-3-5-20241022": {"input": 3.00, "output": 15.00},
+ "claude-haiku-3-5-20241022": {"input": 0.80, "output": 4.00},
+ # Extended thinking models (higher output costs)
+ "claude-sonnet-4-20250514-thinking": {"input": 3.00, "output": 15.00},
+ # Default fallback
+ "default": {"input": 3.00, "output": 15.00},
+}
+
+
+@dataclass
+class CostTracker:
+ """Track AI API costs."""
+
+ total_cost: float = 0.0
+ cost_limit: float = 10.0
+ operations: list[dict] = field(default_factory=list)
+
+ def add_operation(
+ self,
+ input_tokens: int,
+ output_tokens: int,
+ model: str,
+ operation_name: str = "unknown",
+ ) -> float:
+ """
+ Track cost of an AI operation.
+
+ Args:
+ input_tokens: Number of input tokens
+ output_tokens: Number of output tokens
+ model: Model identifier
+ operation_name: Name of operation for tracking
+
+ Returns:
+ Cost of this operation in dollars
+
+ Raises:
+ CostLimitExceeded: If operation would exceed budget
+ """
+ cost = self.calculate_cost(input_tokens, output_tokens, model)
+
+ # Check if this would exceed limit
+ if self.total_cost + cost > self.cost_limit:
+ raise CostLimitExceeded(
+ f"Operation would exceed cost limit: "
+ f"${self.total_cost + cost:.2f} > ${self.cost_limit:.2f}"
+ )
+
+ self.total_cost += cost
+ self.operations.append(
+ {
+ "timestamp": datetime.now().isoformat(),
+ "operation": operation_name,
+ "model": model,
+ "input_tokens": input_tokens,
+ "output_tokens": output_tokens,
+ "cost": cost,
+ }
+ )
+
+ return cost
+
+ @staticmethod
+ def calculate_cost(input_tokens: int, output_tokens: int, model: str) -> float:
+ """
+ Calculate cost for model usage.
+
+ Args:
+ input_tokens: Number of input tokens
+ output_tokens: Number of output tokens
+ model: Model identifier
+
+ Returns:
+ Cost in dollars
+ """
+ # Get pricing for model (fallback to default)
+ pricing = AI_PRICING.get(model, AI_PRICING["default"])
+
+ input_cost = (input_tokens / 1_000_000) * pricing["input"]
+ output_cost = (output_tokens / 1_000_000) * pricing["output"]
+
+ return input_cost + output_cost
+
+ def remaining_budget(self) -> float:
+ """Get remaining budget in dollars."""
+ return max(0.0, self.cost_limit - self.total_cost)
+
+ def usage_report(self) -> str:
+ """Generate cost usage report."""
+ lines = [
+ "Cost Usage Report",
+ "=" * 50,
+ f"Total Cost: ${self.total_cost:.4f}",
+ f"Budget: ${self.cost_limit:.2f}",
+ f"Remaining: ${self.remaining_budget():.4f}",
+ f"Usage: {(self.total_cost / self.cost_limit * 100):.1f}%",
+ "",
+ f"Operations: {len(self.operations)}",
+ ]
+
+ if self.operations:
+ lines.append("")
+ lines.append("Top 5 Most Expensive Operations:")
+ sorted_ops = sorted(self.operations, key=lambda x: x["cost"], reverse=True)
+ for op in sorted_ops[:5]:
+ lines.append(
+ f" ${op['cost']:.4f} - {op['operation']} "
+ f"({op['input_tokens']} in, {op['output_tokens']} out)"
+ )
+
+ return "\n".join(lines)
+
+
+class RateLimiter:
+ """
+ Singleton rate limiter for GitHub automation.
+
+ Manages:
+ - GitHub API rate limits (token bucket)
+ - AI cost limits (budget tracking)
+ - Request queuing and backoff
+ """
+
+ _instance: RateLimiter | None = None
+ _initialized: bool = False
+
+ def __init__(
+ self,
+ github_limit: int = 5000,
+ github_refill_rate: float = 1.4, # ~5000/hour
+ cost_limit: float = 10.0,
+ max_retry_delay: float = 300.0, # 5 minutes
+ ):
+ """
+ Initialize rate limiter.
+
+ Args:
+ github_limit: Maximum GitHub API calls (default: 5000/hour)
+ github_refill_rate: Tokens per second refill rate
+ cost_limit: Maximum AI cost in dollars per run
+ max_retry_delay: Maximum exponential backoff delay
+ """
+ if RateLimiter._initialized:
+ return
+
+ self.github_bucket = TokenBucket(
+ capacity=github_limit,
+ refill_rate=github_refill_rate,
+ )
+ self.cost_tracker = CostTracker(cost_limit=cost_limit)
+ self.max_retry_delay = max_retry_delay
+
+ # Request statistics
+ self.github_requests = 0
+ self.github_rate_limited = 0
+ self.github_errors = 0
+ self.start_time = datetime.now()
+
+ RateLimiter._initialized = True
+
+ @classmethod
+ def get_instance(
+ cls,
+ github_limit: int = 5000,
+ github_refill_rate: float = 1.4,
+ cost_limit: float = 10.0,
+ max_retry_delay: float = 300.0,
+ ) -> RateLimiter:
+ """
+ Get or create singleton instance.
+
+ Args:
+ github_limit: Maximum GitHub API calls
+ github_refill_rate: Tokens per second refill rate
+ cost_limit: Maximum AI cost in dollars
+ max_retry_delay: Maximum retry delay
+
+ Returns:
+ RateLimiter singleton instance
+ """
+ if cls._instance is None:
+ cls._instance = RateLimiter(
+ github_limit=github_limit,
+ github_refill_rate=github_refill_rate,
+ cost_limit=cost_limit,
+ max_retry_delay=max_retry_delay,
+ )
+ return cls._instance
+
+ @classmethod
+ def reset_instance(cls) -> None:
+ """Reset singleton (for testing)."""
+ cls._instance = None
+ cls._initialized = False
+
+ async def acquire_github(self, timeout: float | None = None) -> bool:
+ """
+ Acquire permission for GitHub API call.
+
+ Args:
+ timeout: Maximum time to wait (None = wait forever)
+
+ Returns:
+ True if permission granted, False if timeout
+ """
+ self.github_requests += 1
+ success = await self.github_bucket.acquire(tokens=1, timeout=timeout)
+ if not success:
+ self.github_rate_limited += 1
+ return success
+
+ def check_github_available(self) -> tuple[bool, str]:
+ """
+ Check if GitHub API is available without consuming token.
+
+ Returns:
+ (available, message) tuple
+ """
+ available = self.github_bucket.available()
+
+ if available > 0:
+ return True, f"{available} requests available"
+
+ wait_time = self.github_bucket.time_until_available()
+ return False, f"Rate limited. Wait {wait_time:.1f}s for next request"
+
+ def track_ai_cost(
+ self,
+ input_tokens: int,
+ output_tokens: int,
+ model: str,
+ operation_name: str = "unknown",
+ ) -> float:
+ """
+ Track AI API cost.
+
+ Args:
+ input_tokens: Number of input tokens
+ output_tokens: Number of output tokens
+ model: Model identifier
+ operation_name: Operation name for tracking
+
+ Returns:
+ Cost of operation
+
+ Raises:
+ CostLimitExceeded: If budget exceeded
+ """
+ return self.cost_tracker.add_operation(
+ input_tokens=input_tokens,
+ output_tokens=output_tokens,
+ model=model,
+ operation_name=operation_name,
+ )
+
+ def check_cost_available(self) -> tuple[bool, str]:
+ """
+ Check if cost budget is available.
+
+ Returns:
+ (available, message) tuple
+ """
+ remaining = self.cost_tracker.remaining_budget()
+
+ if remaining > 0:
+ return True, f"${remaining:.2f} budget remaining"
+
+ return False, f"Cost budget exceeded (${self.cost_tracker.total_cost:.2f})"
+
+ def record_github_error(self) -> None:
+ """Record a GitHub API error."""
+ self.github_errors += 1
+
+ def statistics(self) -> dict:
+ """
+ Get rate limiter statistics.
+
+ Returns:
+ Dictionary of statistics
+ """
+ runtime = (datetime.now() - self.start_time).total_seconds()
+
+ return {
+ "runtime_seconds": runtime,
+ "github": {
+ "total_requests": self.github_requests,
+ "rate_limited": self.github_rate_limited,
+ "errors": self.github_errors,
+ "available_tokens": self.github_bucket.available(),
+ "requests_per_second": self.github_requests / max(runtime, 1),
+ },
+ "cost": {
+ "total_cost": self.cost_tracker.total_cost,
+ "budget": self.cost_tracker.cost_limit,
+ "remaining": self.cost_tracker.remaining_budget(),
+ "operations": len(self.cost_tracker.operations),
+ },
+ }
+
+ def report(self) -> str:
+ """Generate comprehensive usage report."""
+ stats = self.statistics()
+ runtime = timedelta(seconds=int(stats["runtime_seconds"]))
+
+ lines = [
+ "Rate Limiter Report",
+ "=" * 60,
+ f"Runtime: {runtime}",
+ "",
+ "GitHub API:",
+ f" Total Requests: {stats['github']['total_requests']}",
+ f" Rate Limited: {stats['github']['rate_limited']}",
+ f" Errors: {stats['github']['errors']}",
+ f" Available Tokens: {stats['github']['available_tokens']}",
+ f" Rate: {stats['github']['requests_per_second']:.2f} req/s",
+ "",
+ "AI Cost:",
+ f" Total: ${stats['cost']['total_cost']:.4f}",
+ f" Budget: ${stats['cost']['budget']:.2f}",
+ f" Remaining: ${stats['cost']['remaining']:.4f}",
+ f" Operations: {stats['cost']['operations']}",
+ "",
+ self.cost_tracker.usage_report(),
+ ]
+
+ return "\n".join(lines)
+
+
+def rate_limited(
+ operation_type: str = "github",
+ max_retries: int = 3,
+ base_delay: float = 1.0,
+) -> Callable[[F], F]:
+ """
+ Decorator to add rate limiting to functions.
+
+ Features:
+ - Pre-flight rate check
+ - Automatic retry with exponential backoff
+ - Error handling for 403/429 responses
+
+ Args:
+ operation_type: Type of operation ("github" or "ai")
+ max_retries: Maximum number of retries
+ base_delay: Base delay for exponential backoff
+
+ Usage:
+ @rate_limited(operation_type="github")
+ async def fetch_pr_data(pr_number: int):
+ result = subprocess.run(["gh", "pr", "view", str(pr_number)])
+ return result
+ """
+
+ def decorator(func: F) -> F:
+ @functools.wraps(func)
+ async def async_wrapper(*args, **kwargs):
+ limiter = RateLimiter.get_instance()
+
+ for attempt in range(max_retries + 1):
+ try:
+ # Pre-flight check
+ if operation_type == "github":
+ available, msg = limiter.check_github_available()
+ if not available and attempt == 0:
+ # Try to acquire (will wait if needed)
+ if not await limiter.acquire_github(timeout=30.0):
+ raise RateLimitExceeded(
+ f"GitHub API rate limit exceeded: {msg}"
+ )
+ elif not available:
+ # On retry, wait for token
+ await limiter.acquire_github(
+ timeout=limiter.max_retry_delay
+ )
+
+ # Execute function
+ result = await func(*args, **kwargs)
+ return result
+
+ except CostLimitExceeded:
+ # Cost limit is hard stop - no retry
+ raise
+
+ except RateLimitExceeded as e:
+ if attempt >= max_retries:
+ raise
+
+ # Exponential backoff
+ delay = min(
+ base_delay * (2**attempt),
+ limiter.max_retry_delay,
+ )
+ print(
+ f"[RateLimit] Retry {attempt + 1}/{max_retries} "
+ f"after {delay:.1f}s: {e}",
+ flush=True,
+ )
+ await asyncio.sleep(delay)
+
+ except Exception as e:
+ # Check if it's a rate limit error (403/429)
+ error_str = str(e).lower()
+ if (
+ "403" in error_str
+ or "429" in error_str
+ or "rate limit" in error_str
+ ):
+ limiter.record_github_error()
+
+ if attempt >= max_retries:
+ raise RateLimitExceeded(
+ f"GitHub API rate limit (HTTP 403/429): {e}"
+ )
+
+ # Exponential backoff
+ delay = min(
+ base_delay * (2**attempt),
+ limiter.max_retry_delay,
+ )
+ print(
+ f"[RateLimit] HTTP 403/429 detected. "
+ f"Retry {attempt + 1}/{max_retries} after {delay:.1f}s",
+ flush=True,
+ )
+ await asyncio.sleep(delay)
+ else:
+ # Not a rate limit error - propagate immediately
+ raise
+
+ @functools.wraps(func)
+ def sync_wrapper(*args, **kwargs):
+ # For sync functions, run in event loop
+ return asyncio.run(async_wrapper(*args, **kwargs))
+
+ # Return appropriate wrapper
+ if asyncio.iscoroutinefunction(func):
+ return async_wrapper # type: ignore
+ else:
+ return sync_wrapper # type: ignore
+
+ return decorator
+
+
+# Convenience function for pre-flight checks
+async def check_rate_limit(operation_type: str = "github") -> None:
+ """
+ Pre-flight rate limit check.
+
+ Args:
+ operation_type: Type of operation to check
+
+ Raises:
+ RateLimitExceeded: If rate limit would be exceeded
+ CostLimitExceeded: If cost budget would be exceeded
+ """
+ limiter = RateLimiter.get_instance()
+
+ if operation_type == "github":
+ available, msg = limiter.check_github_available()
+ if not available:
+ raise RateLimitExceeded(f"GitHub API not available: {msg}")
+
+ elif operation_type == "cost":
+ available, msg = limiter.check_cost_available()
+ if not available:
+ raise CostLimitExceeded(f"Cost budget exceeded: {msg}")
+
+
+# Example usage and testing
+if __name__ == "__main__":
+
+ async def example_usage():
+ """Example of using the rate limiter."""
+
+ # Initialize with custom limits
+ limiter = RateLimiter.get_instance(
+ github_limit=5000,
+ github_refill_rate=1.4,
+ cost_limit=10.0,
+ )
+
+ print("Rate Limiter Example")
+ print("=" * 60)
+
+ # Example 1: Manual rate check
+ print("\n1. Manual rate check:")
+ available, msg = limiter.check_github_available()
+ print(f" GitHub API: {msg}")
+
+ # Example 2: Acquire token
+ print("\n2. Acquire GitHub token:")
+ if await limiter.acquire_github():
+ print(" ✓ Token acquired")
+ else:
+ print(" ✗ Rate limited")
+
+ # Example 3: Track AI cost
+ print("\n3. Track AI cost:")
+ try:
+ cost = limiter.track_ai_cost(
+ input_tokens=1000,
+ output_tokens=500,
+ model="claude-sonnet-4-20250514",
+ operation_name="PR review",
+ )
+ print(f" Cost: ${cost:.4f}")
+ print(
+ f" Remaining budget: ${limiter.cost_tracker.remaining_budget():.2f}"
+ )
+ except CostLimitExceeded as e:
+ print(f" ✗ {e}")
+
+ # Example 4: Decorated function
+ print("\n4. Using @rate_limited decorator:")
+
+ @rate_limited(operation_type="github")
+ async def fetch_github_data(resource: str):
+ print(f" Fetching: {resource}")
+ # Simulate GitHub API call
+ await asyncio.sleep(0.1)
+ return {"data": "example"}
+
+ try:
+ result = await fetch_github_data("pr/123")
+ print(f" Result: {result}")
+ except RateLimitExceeded as e:
+ print(f" ✗ {e}")
+
+ # Final report
+ print("\n" + limiter.report())
+
+ # Run example
+ asyncio.run(example_usage())
diff --git a/apps/backend/runners/github/runner.py b/apps/backend/runners/github/runner.py
new file mode 100644
index 00000000..dabfa4d5
--- /dev/null
+++ b/apps/backend/runners/github/runner.py
@@ -0,0 +1,742 @@
+#!/usr/bin/env python3
+"""
+GitHub Automation Runner
+========================
+
+CLI interface for GitHub automation features:
+- PR Review: AI-powered code review
+- Issue Triage: Classification, duplicate/spam detection
+- Issue Auto-Fix: Automatic spec creation from issues
+- Issue Batching: Group similar issues and create combined specs
+
+Usage:
+ # Review a specific PR
+ python runner.py review-pr 123
+
+ # Triage all open issues
+ python runner.py triage --apply-labels
+
+ # Triage specific issues
+ python runner.py triage 1 2 3
+
+ # Start auto-fix for an issue
+ python runner.py auto-fix 456
+
+ # Check for issues with auto-fix labels
+ python runner.py check-auto-fix-labels
+
+ # Show auto-fix queue
+ python runner.py queue
+
+ # Batch similar issues and create combined specs
+ python runner.py batch-issues
+
+ # Batch specific issues
+ python runner.py batch-issues 1 2 3 4 5
+
+ # Show batch status
+ python runner.py batch-status
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import os
+import sys
+from pathlib import Path
+
+# Add backend to path
+sys.path.insert(0, str(Path(__file__).parent.parent.parent))
+
+# Load .env file
+from dotenv import load_dotenv
+
+env_file = Path(__file__).parent.parent.parent / ".env"
+if env_file.exists():
+ load_dotenv(env_file)
+
+from debug import debug_error
+
+# Add github runner directory to path for direct imports
+sys.path.insert(0, str(Path(__file__).parent))
+
+# Now import models and orchestrator directly (they use relative imports internally)
+from models import GitHubRunnerConfig
+from orchestrator import GitHubOrchestrator, ProgressCallback
+
+
+def print_progress(callback: ProgressCallback) -> None:
+ """Print progress updates to console."""
+ prefix = ""
+ if callback.pr_number:
+ prefix = f"[PR #{callback.pr_number}] "
+ elif callback.issue_number:
+ prefix = f"[Issue #{callback.issue_number}] "
+
+ print(f"{prefix}[{callback.progress:3d}%] {callback.message}", flush=True)
+
+
+def get_config(args) -> GitHubRunnerConfig:
+ """Build config from CLI args and environment."""
+ token = args.token or os.environ.get("GITHUB_TOKEN", "")
+ bot_token = args.bot_token or os.environ.get("GITHUB_BOT_TOKEN")
+ repo = args.repo or os.environ.get("GITHUB_REPO", "")
+
+ if not token:
+ # Try to get from gh CLI
+ import subprocess
+
+ result = subprocess.run(
+ ["gh", "auth", "token"],
+ capture_output=True,
+ text=True,
+ )
+ if result.returncode == 0:
+ token = result.stdout.strip()
+
+ if not repo:
+ # Try to detect from git remote
+ import subprocess
+
+ result = subprocess.run(
+ ["gh", "repo", "view", "--json", "nameWithOwner", "-q", ".nameWithOwner"],
+ cwd=args.project,
+ capture_output=True,
+ text=True,
+ )
+ if result.returncode == 0:
+ repo = result.stdout.strip()
+
+ if not token:
+ print("Error: No GitHub token found. Set GITHUB_TOKEN or run 'gh auth login'")
+ sys.exit(1)
+
+ if not repo:
+ print("Error: No GitHub repo found. Set GITHUB_REPO or run from a git repo.")
+ sys.exit(1)
+
+ return GitHubRunnerConfig(
+ token=token,
+ repo=repo,
+ bot_token=bot_token,
+ model=args.model,
+ thinking_level=args.thinking_level,
+ auto_fix_enabled=getattr(args, "auto_fix_enabled", False),
+ auto_fix_labels=getattr(args, "auto_fix_labels", ["auto-fix"]),
+ auto_post_reviews=getattr(args, "auto_post", False),
+ )
+
+
+async def cmd_review_pr(args) -> int:
+ """Review a pull request."""
+ import sys
+
+ # Force unbuffered output so Electron sees it in real-time
+ sys.stdout.reconfigure(line_buffering=True)
+ sys.stderr.reconfigure(line_buffering=True)
+
+ print(f"[DEBUG] Starting PR review for PR #{args.pr_number}", flush=True)
+ print(f"[DEBUG] Project directory: {args.project}", flush=True)
+
+ print("[DEBUG] Building config...", flush=True)
+ config = get_config(args)
+ print(f"[DEBUG] Config built: repo={config.repo}, model={config.model}", flush=True)
+
+ print("[DEBUG] Creating orchestrator...", flush=True)
+ orchestrator = GitHubOrchestrator(
+ project_dir=args.project,
+ config=config,
+ progress_callback=print_progress,
+ )
+ print("[DEBUG] Orchestrator created", flush=True)
+
+ print(f"[DEBUG] Calling orchestrator.review_pr({args.pr_number})...", flush=True)
+ result = await orchestrator.review_pr(args.pr_number)
+ print(f"[DEBUG] review_pr returned, success={result.success}", flush=True)
+
+ if result.success:
+ print(f"\n{'=' * 60}")
+ print(f"PR #{result.pr_number} Review Complete")
+ print(f"{'=' * 60}")
+ print(f"Status: {result.overall_status}")
+ print(f"Summary: {result.summary}")
+ print(f"Findings: {len(result.findings)}")
+
+ if result.findings:
+ print("\nFindings by severity:")
+ for f in result.findings:
+ emoji = {"critical": "!", "high": "*", "medium": "-", "low": "."}
+ print(
+ f" {emoji.get(f.severity.value, '?')} [{f.severity.value.upper()}] {f.title}"
+ )
+ print(f" File: {f.file}:{f.line}")
+ return 0
+ else:
+ print(f"\nReview failed: {result.error}")
+ return 1
+
+
+async def cmd_followup_review_pr(args) -> int:
+ """Perform a follow-up review of a pull request."""
+ import sys
+
+ # Force unbuffered output so Electron sees it in real-time
+ sys.stdout.reconfigure(line_buffering=True)
+ sys.stderr.reconfigure(line_buffering=True)
+
+ print(f"[DEBUG] Starting follow-up review for PR #{args.pr_number}", flush=True)
+ print(f"[DEBUG] Project directory: {args.project}", flush=True)
+
+ print("[DEBUG] Building config...", flush=True)
+ config = get_config(args)
+ print(f"[DEBUG] Config built: repo={config.repo}, model={config.model}", flush=True)
+
+ print("[DEBUG] Creating orchestrator...", flush=True)
+ orchestrator = GitHubOrchestrator(
+ project_dir=args.project,
+ config=config,
+ progress_callback=print_progress,
+ )
+ print("[DEBUG] Orchestrator created", flush=True)
+
+ print(
+ f"[DEBUG] Calling orchestrator.followup_review_pr({args.pr_number})...",
+ flush=True,
+ )
+
+ try:
+ result = await orchestrator.followup_review_pr(args.pr_number)
+ except ValueError as e:
+ print(f"\nFollow-up review failed: {e}")
+ return 1
+
+ print(f"[DEBUG] followup_review_pr returned, success={result.success}", flush=True)
+
+ if result.success:
+ print(f"\n{'=' * 60}")
+ print(f"PR #{result.pr_number} Follow-up Review Complete")
+ print(f"{'=' * 60}")
+ print(f"Status: {result.overall_status}")
+ print(f"Is Follow-up: {result.is_followup_review}")
+
+ if result.resolved_findings:
+ print(f"Resolved: {len(result.resolved_findings)} finding(s)")
+ if result.unresolved_findings:
+ print(f"Still Open: {len(result.unresolved_findings)} finding(s)")
+ if result.new_findings_since_last_review:
+ print(
+ f"New Issues: {len(result.new_findings_since_last_review)} finding(s)"
+ )
+
+ print(f"\nSummary:\n{result.summary}")
+
+ if result.findings:
+ print("\nRemaining Findings:")
+ for f in result.findings:
+ emoji = {"critical": "!", "high": "*", "medium": "-", "low": "."}
+ print(
+ f" {emoji.get(f.severity.value, '?')} [{f.severity.value.upper()}] {f.title}"
+ )
+ print(f" File: {f.file}:{f.line}")
+ return 0
+ else:
+ print(f"\nFollow-up review failed: {result.error}")
+ return 1
+
+
+async def cmd_triage(args) -> int:
+ """Triage issues."""
+ config = get_config(args)
+ orchestrator = GitHubOrchestrator(
+ project_dir=args.project,
+ config=config,
+ progress_callback=print_progress,
+ )
+
+ issue_numbers = args.issues if args.issues else None
+ results = await orchestrator.triage_issues(
+ issue_numbers=issue_numbers,
+ apply_labels=args.apply_labels,
+ )
+
+ print(f"\n{'=' * 60}")
+ print(f"Triaged {len(results)} issues")
+ print(f"{'=' * 60}")
+
+ for r in results:
+ flags = []
+ if r.is_duplicate:
+ flags.append(f"DUP of #{r.duplicate_of}")
+ if r.is_spam:
+ flags.append("SPAM")
+ if r.is_feature_creep:
+ flags.append("CREEP")
+
+ flag_str = f" [{', '.join(flags)}]" if flags else ""
+ print(
+ f" #{r.issue_number}: {r.category.value} (confidence: {r.confidence:.0%}){flag_str}"
+ )
+
+ if r.labels_to_add:
+ print(f" + Labels: {', '.join(r.labels_to_add)}")
+
+ return 0
+
+
+async def cmd_auto_fix(args) -> int:
+ """Start auto-fix for an issue."""
+ config = get_config(args)
+ config.auto_fix_enabled = True
+ orchestrator = GitHubOrchestrator(
+ project_dir=args.project,
+ config=config,
+ progress_callback=print_progress,
+ )
+
+ state = await orchestrator.auto_fix_issue(args.issue_number)
+
+ print(f"\n{'=' * 60}")
+ print(f"Auto-Fix State for Issue #{state.issue_number}")
+ print(f"{'=' * 60}")
+ print(f"Status: {state.status.value}")
+ if state.spec_id:
+ print(f"Spec ID: {state.spec_id}")
+ if state.pr_number:
+ print(f"PR: #{state.pr_number}")
+ if state.error:
+ print(f"Error: {state.error}")
+
+ return 0
+
+
+async def cmd_check_labels(args) -> int:
+ """Check for issues with auto-fix labels."""
+ config = get_config(args)
+ config.auto_fix_enabled = True
+ orchestrator = GitHubOrchestrator(
+ project_dir=args.project,
+ config=config,
+ progress_callback=print_progress,
+ )
+
+ issues = await orchestrator.check_auto_fix_labels()
+
+ if issues:
+ print(f"Found {len(issues)} issues with auto-fix labels:")
+ for num in issues:
+ print(f" #{num}")
+ else:
+ print("No issues with auto-fix labels found.")
+
+ return 0
+
+
+async def cmd_check_new(args) -> int:
+ """Check for new issues not yet in the auto-fix queue."""
+ config = get_config(args)
+ config.auto_fix_enabled = True
+ orchestrator = GitHubOrchestrator(
+ project_dir=args.project,
+ config=config,
+ progress_callback=print_progress,
+ )
+
+ issues = await orchestrator.check_new_issues()
+
+ print("JSON Output")
+ print(json.dumps(issues))
+
+ return 0
+
+
+async def cmd_queue(args) -> int:
+ """Show auto-fix queue."""
+ config = get_config(args)
+ orchestrator = GitHubOrchestrator(
+ project_dir=args.project,
+ config=config,
+ )
+
+ queue = await orchestrator.get_auto_fix_queue()
+
+ print(f"\n{'=' * 60}")
+ print(f"Auto-Fix Queue ({len(queue)} items)")
+ print(f"{'=' * 60}")
+
+ if not queue:
+ print("Queue is empty.")
+ return 0
+
+ for state in queue:
+ status_emoji = {
+ "pending": "...",
+ "analyzing": "...",
+ "creating_spec": "...",
+ "building": "...",
+ "qa_review": "...",
+ "pr_created": "+++",
+ "completed": "OK",
+ "failed": "ERR",
+ }
+ emoji = status_emoji.get(state.status.value, "???")
+ print(f" [{emoji}] #{state.issue_number}: {state.status.value}")
+ if state.pr_number:
+ print(f" PR: #{state.pr_number}")
+ if state.error:
+ print(f" Error: {state.error[:50]}...")
+
+ return 0
+
+
+async def cmd_batch_issues(args) -> int:
+ """Batch similar issues and create combined specs."""
+ config = get_config(args)
+ config.auto_fix_enabled = True
+ orchestrator = GitHubOrchestrator(
+ project_dir=args.project,
+ config=config,
+ progress_callback=print_progress,
+ )
+
+ issue_numbers = args.issues if args.issues else None
+ batches = await orchestrator.batch_and_fix_issues(issue_numbers)
+
+ print(f"\n{'=' * 60}")
+ print(f"Created {len(batches)} batches from similar issues")
+ print(f"{'=' * 60}")
+
+ if not batches:
+ print("No batches created. Either no issues found or all issues are unique.")
+ return 0
+
+ for batch in batches:
+ issue_nums = ", ".join(f"#{i.issue_number}" for i in batch.issues)
+ print(f"\n Batch: {batch.batch_id}")
+ print(f" Issues: {issue_nums}")
+ print(f" Theme: {batch.theme}")
+ print(f" Status: {batch.status.value}")
+ if batch.spec_id:
+ print(f" Spec: {batch.spec_id}")
+
+ return 0
+
+
+async def cmd_batch_status(args) -> int:
+ """Show batch status."""
+ config = get_config(args)
+ orchestrator = GitHubOrchestrator(
+ project_dir=args.project,
+ config=config,
+ )
+
+ status = await orchestrator.get_batch_status()
+
+ print(f"\n{'=' * 60}")
+ print("Batch Status")
+ print(f"{'=' * 60}")
+ print(f"Total batches: {status.get('total_batches', 0)}")
+ print(f"Pending: {status.get('pending', 0)}")
+ print(f"Processing: {status.get('processing', 0)}")
+ print(f"Completed: {status.get('completed', 0)}")
+ print(f"Failed: {status.get('failed', 0)}")
+
+ return 0
+
+
+async def cmd_analyze_preview(args) -> int:
+ """
+ Analyze issues and preview proposed batches without executing.
+
+ This is the "proactive" workflow for reviewing issue groupings before action.
+ """
+ import json
+
+ config = get_config(args)
+ orchestrator = GitHubOrchestrator(
+ project_dir=args.project,
+ config=config,
+ progress_callback=print_progress,
+ )
+
+ issue_numbers = args.issues if args.issues else None
+ max_issues = getattr(args, "max_issues", 200)
+
+ result = await orchestrator.analyze_issues_preview(
+ issue_numbers=issue_numbers,
+ max_issues=max_issues,
+ )
+
+ if not result.get("success"):
+ print(f"Error: {result.get('error', 'Unknown error')}")
+ return 1
+
+ print(f"\n{'=' * 60}")
+ print("Issue Analysis Preview")
+ print(f"{'=' * 60}")
+ print(f"Total issues: {result.get('total_issues', 0)}")
+ print(f"Analyzed: {result.get('analyzed_issues', 0)}")
+ print(f"Already batched: {result.get('already_batched', 0)}")
+ print(f"Proposed batches: {len(result.get('proposed_batches', []))}")
+ print(f"Single issues: {len(result.get('single_issues', []))}")
+
+ proposed_batches = result.get("proposed_batches", [])
+ if proposed_batches:
+ print(f"\n{'=' * 60}")
+ print("Proposed Batches (for human review)")
+ print(f"{'=' * 60}")
+
+ for i, batch in enumerate(proposed_batches, 1):
+ confidence = batch.get("confidence", 0)
+ validated = "" if batch.get("validated") else "[NEEDS REVIEW] "
+ print(
+ f"\n Batch {i}: {validated}{batch.get('theme', 'No theme')} ({confidence:.0%} confidence)"
+ )
+ print(f" Primary issue: #{batch.get('primary_issue')}")
+ print(f" Issue count: {batch.get('issue_count', 0)}")
+ print(f" Reasoning: {batch.get('reasoning', 'N/A')}")
+ print(" Issues:")
+ for item in batch.get("issues", []):
+ similarity = item.get("similarity_to_primary", 0)
+ print(
+ f" - #{item['issue_number']}: {item.get('title', '?')} ({similarity:.0%})"
+ )
+
+ # Output JSON for programmatic use
+ if getattr(args, "json", False):
+ print(f"\n{'=' * 60}")
+ print("JSON Output")
+ print(f"{'=' * 60}")
+ # Print JSON on single line to avoid corruption from line-by-line stdout prefixes
+ print(json.dumps(result))
+
+ return 0
+
+
+async def cmd_approve_batches(args) -> int:
+ """
+ Approve and execute batches from a JSON file.
+
+ Usage: runner.py approve-batches approved_batches.json
+ """
+ import json
+
+ config = get_config(args)
+ orchestrator = GitHubOrchestrator(
+ project_dir=args.project,
+ config=config,
+ progress_callback=print_progress,
+ )
+
+ # Load approved batches from file
+ try:
+ with open(args.batch_file) as f:
+ approved_batches = json.load(f)
+ except (json.JSONDecodeError, FileNotFoundError) as e:
+ print(f"Error loading batch file: {e}")
+ return 1
+
+ if not approved_batches:
+ print("No batches in file to approve.")
+ return 0
+
+ print(f"Approving and executing {len(approved_batches)} batches...")
+
+ created_batches = await orchestrator.approve_and_execute_batches(approved_batches)
+
+ print(f"\n{'=' * 60}")
+ print(f"Created {len(created_batches)} batches")
+ print(f"{'=' * 60}")
+
+ for batch in created_batches:
+ issue_nums = ", ".join(f"#{i.issue_number}" for i in batch.issues)
+ print(f" {batch.batch_id}: {issue_nums}")
+
+ return 0
+
+
+def main():
+ """CLI entry point."""
+ import argparse
+
+ parser = argparse.ArgumentParser(
+ description="GitHub automation CLI",
+ formatter_class=argparse.RawDescriptionHelpFormatter,
+ )
+
+ # Global options
+ parser.add_argument(
+ "--project",
+ type=Path,
+ default=Path.cwd(),
+ help="Project directory (default: current)",
+ )
+ parser.add_argument(
+ "--token",
+ type=str,
+ help="GitHub token (or set GITHUB_TOKEN)",
+ )
+ parser.add_argument(
+ "--bot-token",
+ type=str,
+ help="Bot account token for comments (optional)",
+ )
+ parser.add_argument(
+ "--repo",
+ type=str,
+ help="GitHub repo (owner/name) or auto-detect",
+ )
+ parser.add_argument(
+ "--model",
+ type=str,
+ default="claude-sonnet-4-20250514",
+ help="AI model to use",
+ )
+ parser.add_argument(
+ "--thinking-level",
+ type=str,
+ default="medium",
+ choices=["none", "low", "medium", "high"],
+ help="Thinking level for extended reasoning",
+ )
+
+ subparsers = parser.add_subparsers(dest="command", help="Command to run")
+
+ # review-pr command
+ review_parser = subparsers.add_parser("review-pr", help="Review a pull request")
+ review_parser.add_argument("pr_number", type=int, help="PR number to review")
+ review_parser.add_argument(
+ "--auto-post",
+ action="store_true",
+ help="Automatically post review to GitHub",
+ )
+
+ # followup-review-pr command
+ followup_parser = subparsers.add_parser(
+ "followup-review-pr",
+ help="Follow-up review of a PR (after contributor changes)",
+ )
+ followup_parser.add_argument("pr_number", type=int, help="PR number to review")
+
+ # triage command
+ triage_parser = subparsers.add_parser("triage", help="Triage issues")
+ triage_parser.add_argument(
+ "issues",
+ type=int,
+ nargs="*",
+ help="Specific issue numbers (or all open if none)",
+ )
+ triage_parser.add_argument(
+ "--apply-labels",
+ action="store_true",
+ help="Apply suggested labels to GitHub",
+ )
+
+ # auto-fix command
+ autofix_parser = subparsers.add_parser("auto-fix", help="Start auto-fix for issue")
+ autofix_parser.add_argument("issue_number", type=int, help="Issue number to fix")
+
+ # check-auto-fix-labels command
+ subparsers.add_parser(
+ "check-auto-fix-labels", help="Check for issues with auto-fix labels"
+ )
+
+ # check-new command
+ subparsers.add_parser(
+ "check-new", help="Check for new issues not yet in auto-fix queue"
+ )
+
+ # queue command
+ subparsers.add_parser("queue", help="Show auto-fix queue")
+
+ # batch-issues command
+ batch_parser = subparsers.add_parser(
+ "batch-issues", help="Batch similar issues and create combined specs"
+ )
+ batch_parser.add_argument(
+ "issues",
+ type=int,
+ nargs="*",
+ help="Specific issue numbers (or all open if none)",
+ )
+
+ # batch-status command
+ subparsers.add_parser("batch-status", help="Show batch status")
+
+ # analyze-preview command (proactive workflow)
+ analyze_parser = subparsers.add_parser(
+ "analyze-preview",
+ help="Analyze issues and preview proposed batches without executing",
+ )
+ analyze_parser.add_argument(
+ "issues",
+ type=int,
+ nargs="*",
+ help="Specific issue numbers (or all open if none)",
+ )
+ analyze_parser.add_argument(
+ "--max-issues",
+ type=int,
+ default=200,
+ help="Maximum number of issues to analyze (default: 200)",
+ )
+ analyze_parser.add_argument(
+ "--json",
+ action="store_true",
+ help="Output JSON for programmatic use",
+ )
+
+ # approve-batches command
+ approve_parser = subparsers.add_parser(
+ "approve-batches",
+ help="Approve and execute batches from a JSON file",
+ )
+ approve_parser.add_argument(
+ "batch_file",
+ type=Path,
+ help="JSON file containing approved batches",
+ )
+
+ args = parser.parse_args()
+
+ if not args.command:
+ parser.print_help()
+ sys.exit(1)
+
+ # Route to command handler
+ commands = {
+ "review-pr": cmd_review_pr,
+ "followup-review-pr": cmd_followup_review_pr,
+ "triage": cmd_triage,
+ "auto-fix": cmd_auto_fix,
+ "check-auto-fix-labels": cmd_check_labels,
+ "check-new": cmd_check_new,
+ "queue": cmd_queue,
+ "batch-issues": cmd_batch_issues,
+ "batch-status": cmd_batch_status,
+ "analyze-preview": cmd_analyze_preview,
+ "approve-batches": cmd_approve_batches,
+ }
+
+ handler = commands.get(args.command)
+ if not handler:
+ print(f"Unknown command: {args.command}")
+ sys.exit(1)
+
+ try:
+ exit_code = asyncio.run(handler(args))
+ sys.exit(exit_code)
+ except KeyboardInterrupt:
+ print("\nInterrupted.")
+ sys.exit(1)
+ except Exception as e:
+ import traceback
+
+ debug_error("github_runner", "Command failed", error=str(e))
+ print(f"Error: {e}")
+ traceback.print_exc()
+ sys.exit(1)
+
+
+if __name__ == "__main__":
+ main()
diff --git a/apps/backend/runners/github/sanitize.py b/apps/backend/runners/github/sanitize.py
new file mode 100644
index 00000000..d8f2d737
--- /dev/null
+++ b/apps/backend/runners/github/sanitize.py
@@ -0,0 +1,570 @@
+"""
+GitHub Content Sanitization
+============================
+
+Protects against prompt injection attacks by:
+- Stripping HTML comments that may contain hidden instructions
+- Enforcing content length limits
+- Escaping special delimiters
+- Validating AI output format before acting
+
+Based on OWASP guidelines for LLM prompt injection prevention.
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import re
+from dataclasses import dataclass
+from typing import Any
+
+logger = logging.getLogger(__name__)
+
+
+# Content length limits
+MAX_ISSUE_BODY_CHARS = 10_000 # 10KB
+MAX_PR_BODY_CHARS = 10_000 # 10KB
+MAX_DIFF_CHARS = 100_000 # 100KB
+MAX_FILE_CONTENT_CHARS = 50_000 # 50KB per file
+MAX_COMMENT_CHARS = 5_000 # 5KB per comment
+
+
+@dataclass
+class SanitizeResult:
+ """Result of sanitization operation."""
+
+ content: str
+ was_truncated: bool
+ was_modified: bool
+ removed_items: list[str] # List of removed elements
+ original_length: int
+ final_length: int
+ warnings: list[str]
+
+ def to_dict(self) -> dict[str, Any]:
+ return {
+ "was_truncated": self.was_truncated,
+ "was_modified": self.was_modified,
+ "removed_items": self.removed_items,
+ "original_length": self.original_length,
+ "final_length": self.final_length,
+ "warnings": self.warnings,
+ }
+
+
+class ContentSanitizer:
+ """
+ Sanitizes user-provided content to prevent prompt injection.
+
+ Usage:
+ sanitizer = ContentSanitizer()
+
+ # Sanitize issue body
+ result = sanitizer.sanitize_issue_body(issue_body)
+ if result.was_modified:
+ logger.warning(f"Content modified: {result.warnings}")
+
+ # Sanitize for prompt inclusion
+ safe_content = sanitizer.wrap_user_content(
+ content=issue_body,
+ content_type="issue_body",
+ )
+ """
+
+ # Patterns for dangerous content
+ HTML_COMMENT_PATTERN = re.compile(r"", re.MULTILINE)
+ SCRIPT_TAG_PATTERN = re.compile(r"