Kill_LIFE/docs/MISTRAL_TOWER_GUIDE.md

Mistral Tower Guide

How Tower manages knowledge in the Kill_LIFE / Mascarade ecosystem

Agent: Tower Agent ID: ag_019d124e760877359ad3ff5031179ebc Model: magistral-medium-latest (temperature 0.4) Domains: docs, readme, specs, content, email, crm, training, research

---

Overview

Tower is the knowledge and content agent of the Mascarade mesh. Its primary responsibilities are:

1. Knowledge management via the knowledge-base MCP server (Memos + Docmost backends)
2. RAG-assisted document retrieval using Mistral Document Library (Beta Libraries)
3. Commercial content generation (formation docs, slide decks, product sheets)
4. Research and analysis tasks (veille technologique, market analysis)

Tower operates with higher creativity (temperature 0.4) than other agents, tuned for long-form text generation and nuanced content production.

---

Knowledge Base MCP Server

Spec: specs/knowledge_base_mcp_spec.md MCP config: mcp.json (entry knowledge-base) Runner: tools/run_knowledge_base_mcp.sh Backend: mascarade/core/mascarade/integrations/knowledge_base.py

Architecture

The knowledge-base MCP server bridges two wiki/note backends:

Backend	Role	URL
Memos	Quick notes, operational memos	Self-hosted
Docmost	Structured documentation, long-form wiki	Self-hosted

MCP tools exposed

Tool	Description
search_pages	Full-text search across both backends
read_page	Retrieve a specific page by ID

These tools are validated via test/test_knowledge_base_mcp.py which confirms server initialization and tool registration.

Integration with Mascarade core

The knowledge-base MCP is used by:

• Core routes: knowledge-base/*
• Knowledge scribe agent: agents/knowledge-scribe/run-and-push
• Tower agent: for RAG context injection before generating content

---

Mistral Document Library (RAG)

Task: T-MS-013 (Plan 24) Client: mascarade/agents/mistral_agents_beta_api.py (MistralLibraryClient)

What it is

Mistral Document Library (Beta Libraries) is Mistral's native RAG solution. Documents uploaded via the Files API are associated with an agent and become searchable context.

How Tower uses it

1. Commercial documents from docs/commercial/ are uploaded to Mistral Files API (T-MS-004)
2. Documents are associated with the Tower agent via Library configuration
3. When Tower receives a query, it automatically searches the library for relevant context
4. RAG-augmented responses include citations from uploaded documents

Commercial documents available

Document	Path
Factory 4.0 Starter	docs/commercial/factory_4_0_starter.md
Factory 4.0 Pro	docs/commercial/factory_4_0_pro.md
Factory 4.0 Enterprise	docs/commercial/factory_4_0_enterprise.md
Factory 4.0 Slide Deck	docs/commercial/factory_4_0_slide_deck.md

Status

• Documents exported to docs/commercial/ (done)
• Upload to Mistral Files API: pending (T-MS-004, requires API call)
• Library association with Tower agent: pending (T-MS-013, depends on T-MS-004)

---

Content Generation Profiles

Tower operates in three content profiles, selectable via dispatch_to_agent.sh:

Writer profile (docs, readme, specs, content, wiki, markdown)

bash tools/ai/dispatch_to_agent.sh --lot T-MS-032 --domain docs

Tasks: documentation pages, README files, technical specifications, wiki content.

Commercial profile (email, crm, commercial, training, formation)

bash tools/ai/dispatch_to_agent.sh --lot T-MS-004 --domain commercial

Tasks: formation documents, product sheets, email templates, CRM content, lead scoring with RAG context.

Researcher profile (research, veille, analysis)

bash tools/ai/dispatch_to_agent.sh --lot T-MS-032 --domain research

Tasks: technology watch, competitor analysis, market research synthesis.

---

Dispatch via dispatch_to_agent.sh

Location: tools/ai/dispatch_to_agent.sh

# Documentation task
bash tools/ai/dispatch_to_agent.sh --lot T-MS-032 --domain docs --prompt "Draft the Mistral Studio Overview page"

# Commercial content with local model (zero cost)
bash tools/ai/dispatch_to_agent.sh --lot T-MS-004 --domain commercial --local

# Research task
bash tools/ai/dispatch_to_agent.sh --lot T-MS-032 --domain research

# Dry run to inspect prompt
bash tools/ai/dispatch_to_agent.sh --lot T-MS-032 --domain docs --dry-run

---

RAG Pipeline (future state)

Once T-MS-004 and T-MS-013 are completed, the Tower RAG pipeline will operate as follows:

User query
  |
  v
Tower agent (magistral-medium-latest, temp 0.4)
  |
  +-> Mistral Document Library search (RAG)
  |     |
  |     +-> docs/commercial/* (uploaded PDFs/markdown)
  |     +-> Outline wiki pages (if connected)
  |
  +-> knowledge-base MCP search
  |     |
  |     +-> Memos (quick notes)
  |     +-> Docmost (structured docs)
  |
  v
RAG-augmented response with citations

---

Key files

File	Purpose
tools/ai/dispatch_to_agent.sh	Agent dispatch (Tower domains: docs, commercial, research)
tools/run_knowledge_base_mcp.sh	Knowledge-base MCP server runner
specs/knowledge_base_mcp_spec.md	MCP server specification
test/test_knowledge_base_mcp.py	MCP server tests
docs/commercial/*.md	Commercial documents for RAG upload
mcp.json	MCP server configuration (includes knowledge-base entry)