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CI for AI coding context: generate AGENTS.md, CLAUDE.md, CODEX.md, and readiness checks for coding agents.

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Agent Ready

Agent Ready hero

agent-ready demo output

Agent Ready is CI for AI coding context. It scans a repository and generates the context files AI coding agents need before they touch code.

README for agents, kept up to date.

It creates:

  • AGENTS.md
  • CLAUDE.md
  • CODEX.md
  • .agent/context.json
  • .agent/checklist.md

🔍 Why This Exists

Claude Code, Codex, OpenClaw, Cursor, and other coding agents work better when the repository explains itself. Most repos do not have a clear agent guide, so agents waste time guessing:

  • what stack is this?
  • how do I run tests?
  • where are risky files?
  • what should I read before editing?
  • what should I avoid changing casually?

Agent Ready turns that repo knowledge into small, reviewable files.

⚡ Install

python3 -m pip install agent-ready

For local development:

python3 -m venv .venv
. .venv/bin/activate
python -m pip install -e '.[dev]'
make test PYTHON=.venv/bin/python
make lint PYTHON=.venv/bin/python
make build PYTHON=.venv/bin/python
make check AGENT_READY=.venv/bin/agent-ready
make score AGENT_READY=.venv/bin/agent-ready

🚀 Quick Start

Preview a repo summary:

agent-ready . --json

Generate agent context files:

agent-ready . --write

Overwrite existing generated files:

agent-ready . --write --force

Check whether generated files are missing or stale in CI:

agent-ready . --check

Print an agent-readiness score with recommendations:

agent-ready . --score
agent-ready . --json --score

Skip project-specific generated or vendor directories during a scan:

agent-ready . --json --ignore fixtures --ignore examples/generated

--check exits with status 1 and lists the files to regenerate when repo context changed.

📊 Demo Output

$ agent-ready . --score
agent-readiness: 100/100 (A)
$ agent-ready . --check
agent-ready files are current

🏗️ Architecture

flowchart LR
    Repo[Repository] --> Scanner[agent-ready scanner]
    Scanner --> Evidence[Evidence map: stack, commands, risks]
    Evidence --> Generator[Context generator]
    Generator --> Outputs[AGENTS.md / CLAUDE.md / CODEX.md / .agent]
    Outputs --> Check[agent-ready --check]
    Check --> CI[CI drift gate]
Loading

The scanner uses local repository evidence such as package files, CI workflows, source extensions, and risk patterns. Generated outputs stay reviewable, small, and safe to commit.

For deeper product positioning and market research, see docs/product-research.md. The maintainable diagram source is in docs/architecture.mmd.

✅ GitHub Action

Use this repository as a composite action to block stale agent context in CI:

name: agent-ready
on: [push, pull_request]
jobs:
  check:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: Adamchaua/agent-ready@v0.1.0
        with:
          mode: check

Other modes:

with:
  mode: score      # print score
  # mode: json-score
  # mode: refresh

🧠 What It Detects

  • languages
  • frameworks
  • package managers
  • test commands
  • build commands
  • lint commands
  • GitHub Actions workflows
  • important files
  • risky areas such as auth, payments, env files, deployments, and migrations
  • top-level directories that matter to agents

📦 Generated Deliverables

AGENTS.md
CLAUDE.md
CODEX.md
.agent/context.json
.agent/checklist.md

AGENTS.md gives all agents a shared operating guide.

CLAUDE.md focuses on Claude Code behavior and safe verification.

CODEX.md focuses on careful coding-agent workflow.

.agent/context.json is machine-readable context for future tools and MCP servers.

.agent/checklist.md is a lightweight QA checklist before PRs or final answers.

🧪 Quality Gate

Before publishing this repo, Agent Ready was checked against these questions:

  • Who needs it? Developers using Claude Code, Codex, OpenClaw, Cursor, or local coding agents.
  • What pain does it solve? Agents lack repo context and often guess commands, risky files, and workflow.
  • Why not just write docs manually? Manual docs are good, but many repos have none. This gives a fast first draft.
  • Can a user run it in five minutes? Yes: install, run agent-ready . --write, review generated files.
  • What can go wrong? Detection is heuristic. Users should review output before committing.

🛡️ Security Notes

Agent Ready does not send repository content anywhere. It scans local file names and small config files only.

Recommended use:

  • review generated files before committing,
  • do not commit real .env files,
  • treat generated risk areas as prompts for human review, not absolute truth,
  • run inside a trusted local checkout.

🗺️ Roadmap

  • OpenClaw profile
  • MCP server from .agent/context.json
  • VS Code extension
  • monorepo service map
  • ownership/team map
  • config file for custom rules
  • GitHub Action that checks whether a repo is agent-ready
  • richer CI snippets for agent-ready . --check

💛 Support

If this helps your agents make fewer mistakes, support is optional and appreciated:

  • EVM: 0x1ecab01075f3bdf1b56b7d849c8e28ef88943624
  • PayPal: ckelvinkhanh32@gmail.com

📄 License

MIT

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CI for AI coding context: generate AGENTS.md, CLAUDE.md, CODEX.md, and readiness checks for coding agents.

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