ai-ready
**ANALYSIS SKILL** — Analyze any repository and generate AI-ready configuration — AGENTS.md, copilot-instructions.md, skills, CI workflows, issue templates. WHEN: \"make this repo ai-ready\", \"set up AI config\", \"add copilot instructions\", \"prepare this repo for AI contributions\", \"generate AGENTS.md\". INVOKES: glob, grep, view, create, edit for repo analysis and file generation. FOR SINGLE OPERATIONS: use create/edit directly for individual config files.
Profile →npx skills add johnpapa/ai-ready --skill ai-ready --agent copilot
Same command for any agent — swap --agent for claude-code, codex, cursor.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# AI-Ready Repo Skill ## Persona Adopt the perspective of an experienced repo maintainer who has managed high-traffic repos and reviewed thousands of PRs. Prioritize what **reduces review burden and contributor friction**. Every file you generate should earn its place — generic boilerplate creates noise. --- Follow these steps in order to analyze the current repository and generate all missing AI-ready configuration assets. **First run vs. re-run:** On the first run, most assets will be missing — the skill creates them. On re-runs, it **audits** existing assets against the current codebase, checking for drift, stale content, and new conventions from recent PR reviews. The skill **never overwrites existing files without user approval**. **Skipping assets:** If the user's prompt mentions skipping specific assets (e.g., "skip CI and issue templates"), respect those exclusions. Still run the full analysis, but skip generation for the excluded assets. **Report-only mode:** If the user asks for a report without generating files (e.g., "how ai-ready is this repo?", "score this repo"), run the full analysis (Steps 0–1) and display the report (Step 11) — but skip all generation steps (Steps
- Persona
- The 12 tracked assets
- Step 0 — Detect GitHub context automatically
- 0a. Identify the repo
- 0b–0d. Fetch metadata, mine PR reviews, check community health
- Step 1 — Analyze the codebase
- 1a. Detect languages, frameworks, and repo type
- 1b. Detect test setup
- 1c. Detect CI/CD
- 1d. Check existing AI configuration
- 1e. Check repo configuration
- 1f–1g. Evaluate changelog and documentation
- 1h. Scan directory structure
- 1i. Compile findings
What does the ai-ready skill do?
**ANALYSIS SKILL** — Analyze any repository and generate AI-ready configuration — AGENTS.md, copilot-instructions.md, skills, CI workflows, issue templates. WHEN: \"make this repo ai-ready\", \"set up AI config\", \"add copilot instructions\", \"prepare this repo for AI contributions\", \"generate AGENTS.md\". INVOKES: glob, grep, view, create, edit for repo analysis and file generation. FOR SINGLE OPERATIONS: use create/edit directly for individual config files.
How do I install it?
Run `npx skills add johnpapa/ai-ready --skill ai-ready --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From johnpapa/ai-ready, a repository with 112 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.