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Tiny router-first context files for AI coding agents (Claude Code, Codex, Gemini CLI, Copilot, Cursor)

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agentinit

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Scaffold hardened, router-first context files so your AI coding agents stop guessing and start delivering.

Pure Python standard library. No runtime dependencies. Generates 2026-ready manifests for Claude Code, Cursor, Copilot, Gemini CLI, and Windsurf.

🚀 Start in 60 seconds

# 1. Install via pipx (recommended)
pipx install agentinit

# 2. Initialize hardened context in your project
cd your-project
agentinit init --minimal

What it does

Instead of giant, token-heavy instruction files, agentinit implements a hierarchical context strategy. It creates a machine-readable map of your project and enforces autonomy via Hardened Mandates.

your-project/
├── llms.txt               # The "robots.txt" for AI (Discovery Index)
├── AGENTS.md              # The central hub with Hardened Mandates
├── CLAUDE.md              # Claude Code router
├── GEMINI.md              # Gemini CLI router
└── docs/
    ├── PROJECT.md         # What this project is
    ├── CONVENTIONS.md     # How to work in it
    └── STATE.md           # Persistent working memory (AI-readable)

Next steps: Open docs/PROJECT.md and docs/CONVENTIONS.md and fill them in.

Next session: Your agent will find llms.txt, read your rules in AGENTS.md, and follow the mandates to autonomously maintain docs/STATE.md and docs/TODO.md.

Troubleshooting: files not visible to your agent

Some agents only scan tracked files. If your agent says it can't find your context:

  • Track everything: Add the manifests so your agent can see them.

    git add llms.txt AGENTS.md CLAUDE.md GEMINI.md docs/
    git add .agents/  # if you added extras
  • Verify ignores: Run git status --ignored to see if your .gitignore is hiding them.

Minimal .gitignore exceptions
!llms.txt
!AGENTS.md
!CLAUDE.md
!GEMINI.md
!docs/PROJECT.md
!docs/CONVENTIONS.md
!docs/TODO.md
!docs/DECISIONS.md
!docs/STATE.md
!.agents/
!.agents/**

🛠️ Add extras (Skills, MCP, Personality)

Agents can do more than just read conventions. Inject modular, hardened resources directly into your project.

# View available resources
agentinit add --list

# Add specific capabilities
agentinit add skill code-reviewer
agentinit add security
agentinit add soul "YourAgentName"

Resources in .agents/ are automatically linked in AGENTS.md and use Imperative Mandates (MUST ALWAYS, MUST NEVER) to ensure compliance and zero-sycophancy.


🚦 Keep your context clean (Status & CI)

Token limits matter. agentinit includes a validator to prevent context bloat, broken links, and missing information.

# View line budgets, broken references, and missing details
agentinit status

# Perfect for CI (exits non-zero on violations)
agentinit status --check

🤖 AI Prompt: Fill the docs fast

After running agentinit init, paste this to your favorite AI agent:

Read the entire repository. Fill in docs/PROJECT.md and docs/CONVENTIONS.md using only facts found in the repo (package files, configs, source code, CI). Do not invent commands. If information is missing, write TODO: <what's needed>. Update docs/STATE.md and docs/TODO.md to reflect our current progress. Do not modify any other files.


📚 Advanced Usage & Commands

Core Commands

  • agentinit init — Add missing files to an existing directory.
  • agentinit minimal — Shortcut for init --minimal.
  • agentinit status — Check health, line budgets, and broken links.
  • agentinit add <type> <name> — Add modular resources (skills, mcp, security, soul).
  • agentinit new <project> — Create a new directory and scaffold files.
  • agentinit remove — Safely remove or archive agent files.

Common Flags

  • --detect — Auto-detect stack and commands from package files (e.g., package.json, pyproject.toml).
  • --yes / -y — Runs non-interactively and skips the wizard.
  • --purpose "<text>" — Prefill the project purpose non-interactively.
💡 Why Hardened Context?
  • Agent Autonomy: Explicit mandates (YOU MUST ALWAYS read state.md) transform the agent from a chatbot into a disciplined project maintainer.
  • AI-Discovery Index: llms.txt ensures any tool (Cursor, Windsurf, Claude) immediately understands your project map.
  • Progressive Disclosure: Keeps the context window high-signal by loading deep details only when relevant.
  • Zero Sycophancy: Mandates force the agent to skip "I'd be happy to help!" and jump straight to the technical solution.
⚙️ Installation & Development

Requires Python 3.10+.

# Install (pipx is recommended)
pipx install agentinit

# Update
pipx upgrade agentinit

Development

pip install -e . --group dev
python3 -m pytest tests/ -v

License

MIT

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