Get instructions for installing and reviewing the full ai-ready skill in Copilot CLI. This wrapper explains how to add the latest version, reload skills, and request repository preparation for AI contributions.
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Make any repo AI-ready — analyzes your codebase and generates AGENTS.md, copilot-instructions.md, CI workflows, issue templates, and more. Mines your PR review patterns and creates files customized to your stack. USE THIS SKILL when the user asks to "make this repo ai-ready", "set up AI config", or "prepare this repo for AI contributions".
安装前可以查看交给 AI 代理的指令内容。
This skill helps the user install the latest ai-ready skill by John Papa.
Why?: The full ai-ready skill is ~600 lines of detailed instructions that evolve frequently. This wrapper keeps it discoverable here while the source of truth stays in johnpapa/ai-ready — always up to date.
Tell the user to add the skill by running this command inside Copilot CLI:
/skills add johnpapa/ai-ready
This downloads the latest version of the skill to their personal skills directory. Re-running the command updates to the latest version.
Remind the user to review the skill before loading it. They can inspect it with:
head -20 ~/.copilot/skills/ai-ready/SKILL.md
After the user confirms they've reviewed and installed it, tell them to reload skills with /skills reload and then say make this repo ai-ready.
Do not run the command on the user's behalf. The user must run it themselves.
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Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.
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Assess a repository’s readiness for AI agents with AgentRC and generate a standalone HTML dashboard. Review scores across nine areas, see prioritized improvements, and optionally apply scoring policies tailored to an organization.
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Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.
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Customize AgentRC readiness assessments to match team or organization standards. Choose or create policies that adjust check importance, disable irrelevant checks, set pass thresholds, and define requirements for automated checks in CI workflows.
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Analyze supplied ad performance data to identify wasted spend, strong campaigns, and next tests. Compare channels, assess whether test differences are meaningful, and produce budget reallocation recommendations with a prioritized action plan.
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Turn code files into learning resources by adding comments that explain syntax, programming concepts, and design choices. Adjust explanation depth and repetition to the reader’s knowledge while preserving file structure, encoding, and syntax.
中文简介正在准备中。当前显示英语简介。