AI Ready

An Agent Skill that analyzes your repository and generates the configuration files AI agents need to contribute correctly. GitHub-native — it auto-discovers your repo's context, community health, and PR review patterns without you explaining anything.

Works in GitHub Copilot, Claude Code, OpenAI Codex, Cursor, and any other tool that supports the Agent Skills standard.

Quick Start

Any agent, one command

The open skills CLI installs into Claude Code, Codex, Cursor, Copilot, and 70+ other agents:

npx skills add johnpapa/ai-ready

That's it — no per-tool setup. Restart your agent afterward.

Native plugin installs

Prefer your tool's own plugin system? Each of these installs the same skill.

Claude and Codex each need two commands — the first registers the marketplace, the second installs the plugin from it.

Copilot CLI installs from the built-in awesome-copilot marketplace. Installing straight from a repo (copilot plugin install johnpapa/ai-ready) still works but is deprecated, so prefer the marketplace form.

~/.agents/skills/ is the vendor-neutral Agent Skills directory that Codex and Cursor both read, so the last row works for most tools.

If a marketplace mirrors this skill, it should point to a release tag such as v1.3.0, not a raw commit SHA.

Then type

make this repo ai-ready

Or invoke it explicitly:

When installed as a plugin from a marketplace, Claude namespaces it as /ai-ready:ai-ready.

The skill analyzes your code, CI, tests, docs, and structure, then generates assets customized to your project — not generic templates.

Run it again anytime

The skill is safe to re-run. On the first run, it creates missing assets. On subsequent runs, it audits your existing AI-ready files against the current state of your codebase — flagging drift like outdated build commands, stale repo structure, or new PR review patterns that should become conventions. It never overwrites your files — it suggests updates and lets you decide.

Keeping updated

Troubleshooting

/plugin marketplace add https://github.com/johnpapa/ai-ready

git config --global url."https://github.com/".insteadOf git@github.com:

Skip what you don't need

Add exclusions to your prompt and the skill will respect them:

make this repo ai-ready but skip CI and issue templates

just generate AGENTS.md and copilot-instructions

Report only

Just want to see where you stand? Ask for a report without generating any files:

how ai-ready is this repo?

score this repo

What to Expect

After you run the skill, you get a full AI-readiness report — analysis, proposed changes, and a projected score. Here's what it looks like for vscode-peacock:

🔗 View the interactive version — collapsible sections, responsive layout, works on mobile.

The report shows:

1. Your Repo Today — current score, what's nailed, what's missing, and why it matters
2. What I'd Like To Do — proposed files to create (nothing changes until you say so)
3. If You Accept — projected score with category breakdown
4. Ready? — offer to create a PR with all the changes

Issue/PR messages generated by this skill always include explicit attribution to the AI Ready skill. It also keeps related docs aligned to repo standards and proactively attempts conflict resolution before opening PRs (or asks when manual help is needed).

📄 Also available as terminal output — same content, rendered in the CLI.

Scoring

Your score is simple: how many of the 12 tracked assets are nailed. That's it — no formulas, no weights.

Why

Contributors (human and AI) show up to your repo and don't know the conventions. They submit PRs that miss tests, break patterns, skip docs. You leave the same review comments on every PR. AI agents make this more challenging — they generate PRs faster, but without context, those PRs create more review burden.

It's the same gap from both sides: contributors don't know what maintainers expect, and maintainers keep re-teaching it. This skill closes that gap by generating repo-level configuration that teaches everyone — human and AI — how to work in the repo correctly. It even mines your PR review comments for repeated feedback and turns them into automated conventions. The result: a 45-minute review becomes a 5-minute review.

Built from Real Maintainer Experience

This skill isn't theoretical — it's shaped by John Papa's experience maintaining popular open source projects and repos at large enterprises. The skill is tuned to prioritize what actually reduces review burden: maintenance matrices that catch the files contributors always forget, conventions mined from the PR feedback you're tired of repeating, and CI that catches problems before you have to.

How It Works — GitHub-Native by Default

You shouldn't have to explain to an AI tool that you're in a GitHub repo. This skill assumes it, and leverages everything GitHub already knows about your project.

Auto-Discovery (zero user input)

The skill starts by pulling context directly from GitHub — no questions asked:

It then scans your local codebase for deeper details — manifest files, test configs, directory structure, existing AI configuration — and combines both into a complete picture.

PR Review Mining — The Killer Feature

This is the highest-value thing the skill does. It reads your recent PR review threads and looks for repeated feedback — the same comments you leave on every PR:

• "Please add tests for new features" → becomes a test convention rule
• "Use the X pattern instead of Y" → becomes a coding convention rule
• "Don't forget to update the changelog" → becomes a maintenance matrix entry
• "This breaks on mobile, check responsive layout" → becomes a screen size rule

These mined conventions go directly into copilot-instructions.md. The next AI-generated PR follows those rules automatically. You stop repeating yourself.

What Gets Generated

Every file is customized to your repo's actual language, framework, and patterns — not generic boilerplate. The skill only creates files that don't already exist.

Two Layers of PR Quality

The assets this skill generates enable two complementary layers of PR quality — one you get automatically, one you enable:

Together: PRs are validated for correctness (CI) and reviewed for quality (Copilot). This skill generates the inputs for both — the CI workflow and the conventions file that Copilot code review reads.

To enable Copilot code review: go to your repo's Settings → Copilot → Code review and turn it on. Once enabled, every PR is automatically reviewed against the conventions in copilot-instructions.md.

Tested Against

This skill has been validated against a diverse set of repos — courses, applications, VS Code extensions, monorepos, and more. See skills/ai-ready/references/training-repos.md for the full list.

Contributing

Quick Start

1. Fork this repo and create a branch
2. Make your changes (skills or docs)
3. Test locally: copy skills/ai-ready/SKILL.md to ~/.copilot/skills/ai-ready/SKILL.md, start copilot, then say "make this repo ai-ready"
4. Open a PR

See AGENTS.md for the full contributor guide.

Credits

This skill was strengthened using:

• Sensei — AI skill quality scorer that evaluates frontmatter, structure, and discoverability. Used to achieve a "High" rating.
• Agent Skills Spec — GitHub's specification for skill authoring. Used to refactor from 964 lines to a 225-line spec-compliant structure with progressive disclosure.

License

MIT