StillKnotKnown
d024eec105
* fix(merge): resolve multiple merge-related issues (ACS-194, ACS-179, ACS-174, ACS-163)
- ACS-179: Fix TypeError in print_conflict_info - handle both string and dict conflict formats
- ACS-174: Handle git hook failures during merge - skip checkout if already on target branch
- ACS-163: Fix merge failure fallthrough - return False immediately when merge fails
- ACS-194: Improve AI merge success rate - add Haiku→Sonnet fallback with enhanced prompts
All fixes include regression tests.
* fix: improve merge robustness and fix test issues
This commit addresses multiple issues related to merge functionality
and test quality:
1. workspace.py:
- Fix case-insensitive natural language pattern matching to detect
AI explanations returned instead of code
2. worktree.py:
- Guard against None stderr when handling git hook failures
- Improve error messages for merge hook handling
3. workspace/display.py:
- Improve print_conflict_info() to properly categorize conflicts
(marker vs AI merge failures)
- Add severity indicators (🔴 for high, 🟡 for medium)
- Use shlex.quote() for proper git add command quoting
- Provide clearer guidance for different conflict types
4. tests/test_merge_ai_resolver.py:
- Fix test assertions to match actual AI_MERGE_SYSTEM_PROMPT content
(check for "intelligently" and "task's intent" instead of
non-existent "semantic understanding")
5. tests/test_workspace.py:
- Add side-effect verification for merge failure tests
- Remove unused fixtures
- Add assertions for severity emoji indicators
6. tests/test_worktree.py:
- Add subprocess return code checks for better test reliability
Related: ACS-194, ACS-179, ACS-174, ACS-163
* fix: improve display formatting and use proper imports
1. display.py:
- Fix trailing space when severity_icon is empty (low/unknown severity)
- Only add leading space to icon when icon is non-empty
2. workspace/__init__.py:
- Export AI_MERGE_SYSTEM_PROMPT and _build_merge_prompt
- Add to __all__ for public API access
3. test_merge_ai_resolver.py:
- Use standard imports from core.workspace package
- Remove fragile importlib.util dynamic loading
* fix: address all 6 review findings
1. workspace.py:
- Fix parameter naming: max_thinking -> max_thinking_tokens
(matches codebase convention used in 25+ locations)
- Extract hardcoded model constants: MERGE_FAST_MODEL,
MERGE_CAPABLE_MODEL, MERGE_FAST_THINKING, MERGE_COMPLEX_THINKING
- Improve natural language detection: check patterns at START of line
and require absence of code patterns to reduce false positives
2. display.py:
- Add critical severity icon handling (⛔ for critical severity)
3. worktree.py:
- Fix inconsistent stderr handling: use truthiness check for both
branches (empty strings show '<no stderr>')
4. test_workspace.py:
- Remove unused imports: patch, MagicMock from unittest.mock
Related: ACS-194
---------
Co-authored-by: StillKnotKnown <stillknotknown@users.noreply.github.com>
Co-authored-by: Andy <119136210+AndyMik90@users.noreply.github.com>
Auto Claude
Autonomous multi-agent coding framework that plans, builds, and validates software for you.
Download
Stable Release
| Platform | Download |
|---|---|
| Windows | Auto-Claude-2.7.2-win32-x64.exe |
| macOS (Apple Silicon) | Auto-Claude-2.7.2-darwin-arm64.dmg |
| macOS (Intel) | Auto-Claude-2.7.2-darwin-x64.dmg |
| Linux | Auto-Claude-2.7.2-linux-x86_64.AppImage |
| Linux (Debian) | Auto-Claude-2.7.2-linux-amd64.deb |
Beta Release
⚠️ Beta releases may contain bugs and breaking changes. View all releases
| Platform | Download |
|---|---|
| Windows | Auto-Claude-2.7.2-beta.10-win32-x64.exe |
| macOS (Apple Silicon) | Auto-Claude-2.7.2-beta.10-darwin-arm64.dmg |
| macOS (Intel) | Auto-Claude-2.7.2-beta.10-darwin-x64.dmg |
| Linux | Auto-Claude-2.7.2-beta.10-linux-x86_64.AppImage |
| Linux (Debian) | Auto-Claude-2.7.2-beta.10-linux-amd64.deb |
| Linux (Flatpak) | Auto-Claude-2.7.2-beta.10-linux-x86_64.flatpak |
All releases include SHA256 checksums and VirusTotal scan results for security verification.
Requirements
- Claude Pro/Max subscription - Get one here
- Claude Code CLI -
npm install -g @anthropic-ai/claude-code - Git repository - Your project must be initialized as a git repo
Quick Start
- Download and install the app for your platform
- Open your project - Select a git repository folder
- Connect Claude - The app will guide you through OAuth setup
- Create a task - Describe what you want to build
- Watch it work - Agents plan, code, and validate autonomously
Features
| Feature | Description |
|---|---|
| Autonomous Tasks | Describe your goal; agents handle planning, implementation, and validation |
| Parallel Execution | Run multiple builds simultaneously with up to 12 agent terminals |
| Isolated Workspaces | All changes happen in git worktrees - your main branch stays safe |
| Self-Validating QA | Built-in quality assurance loop catches issues before you review |
| AI-Powered Merge | Automatic conflict resolution when integrating back to main |
| Memory Layer | Agents retain insights across sessions for smarter builds |
| GitHub/GitLab Integration | Import issues, investigate with AI, create merge requests |
| Linear Integration | Sync tasks with Linear for team progress tracking |
| Cross-Platform | Native desktop apps for Windows, macOS, and Linux |
| Auto-Updates | App updates automatically when new versions are released |
Interface
Kanban Board
Visual task management from planning through completion. Create tasks and monitor agent progress in real-time.
Agent Terminals
AI-powered terminals with one-click task context injection. Spawn multiple agents for parallel work.
Roadmap
AI-assisted feature planning with competitor analysis and audience targeting.
Additional Features
- Insights - Chat interface for exploring your codebase
- Ideation - Discover improvements, performance issues, and vulnerabilities
- Changelog - Generate release notes from completed tasks
Project Structure
Auto-Claude/
├── apps/
│ ├── backend/ # Python agents, specs, QA pipeline
│ └── frontend/ # Electron desktop application
├── guides/ # Additional documentation
├── tests/ # Test suite
└── scripts/ # Build utilities
CLI Usage
For headless operation, CI/CD integration, or terminal-only workflows:
cd apps/backend
# Create a spec interactively
python spec_runner.py --interactive
# Run autonomous build
python run.py --spec 001
# Review and merge
python run.py --spec 001 --review
python run.py --spec 001 --merge
See guides/CLI-USAGE.md for complete CLI documentation.
Development
Want to build from source or contribute? See CONTRIBUTING.md for complete development setup instructions.
For Linux-specific builds (Flatpak, AppImage), see guides/linux.md.
Security
Auto Claude uses a three-layer security model:
- OS Sandbox - Bash commands run in isolation
- Filesystem Restrictions - Operations limited to project directory
- Dynamic Command Allowlist - Only approved commands based on detected project stack
All releases are:
- Scanned with VirusTotal before publishing
- Include SHA256 checksums for verification
- Code-signed where applicable (macOS)
Available Scripts
| Command | Description |
|---|---|
npm run install:all |
Install backend and frontend dependencies |
npm start |
Build and run the desktop app |
npm run dev |
Run in development mode with hot reload |
npm run package |
Package for current platform |
npm run package:mac |
Package for macOS |
npm run package:win |
Package for Windows |
npm run package:linux |
Package for Linux |
npm run package:flatpak |
Package as Flatpak (see guides/linux.md) |
npm run lint |
Run linter |
npm test |
Run frontend tests |
npm run test:backend |
Run backend tests |
Contributing
We welcome contributions! Please read CONTRIBUTING.md for:
- Development setup instructions
- Code style guidelines
- Testing requirements
- Pull request process
Community
- Discord - Join our community
- Issues - Report bugs or request features
- Discussions - Ask questions
License
AGPL-3.0 - GNU Affero General Public License v3.0
Auto Claude is free to use. If you modify and distribute it, or run it as a service, your code must also be open source under AGPL-3.0.
Commercial licensing available for closed-source use cases.
