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bootstrap

Skill2 starsChanged 3 months agoMITView on GitHub

Deploy Botte Secrète's token-saving stack into a target project — wire the botte-llm MCP server into .mcp.json, audit the project's agent directives, and write a .botte config + setup report. Use when the user wants to "install botte", "set up token savings on a project", reduce an existing project's token/cost usage, or onboard a repo to local-first routing. This is the capstone that makes the toolkit actually save money on real projects.

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SKILL.md

bootstrap — deploy the toolkit into a project

The whole point of Botte Secrète is to make real projects cheaper to work on. This installs the stack into any project in one command.

Run it

python -m skills.bootstrap.cli /path/to/project
python -m skills.bootstrap.cli /path/to/project --create-agents-md   # scaffold AGENTS.md if missing
python -m skills.bootstrap.cli /path/to/project --scan-subnet --json

What it does (idempotent)

  1. Discover local backends (llm_backends) so routing has somewhere to send work.
  2. Wire MCP — merges the botte-llm server into the project's .mcp.json (non-destructive; keeps any existing servers). The project's agent then gains: auto_route, local_chat, fusion, find_skills, audit_local_usage, route_task, discover_backends, list_models.
  3. Audit directives (directives_audit) — reports the CLAUDE.md/AGENTS.md health; with --create-agents-md, scaffolds a starter AGENTS.md when none exists.
  4. Write .botte/config.json — chosen local model, detected cloud keys, token budget, routing mode (auto).
  5. Write .botte/setup-report.json + print a summary with next steps.

Result

The project's agent now routes cheap work (classification, extraction, summaries, tool/skill search) to local models for 0 cloud tokens, escalates only the hard parts to the cloud (auto_router), and picks tools with find_skills instead of reading every skill description with the expensive model.

.mcp.json and .botte/ hold per-machine absolute paths, so they are gitignored in this repo — deploy on each machine.

Related: [[llm_mcp]] (the tools wired in), [[auto_router]], [[skill_finder]], [[directives_audit]], [[llm_backends]].

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