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acreadiness-assess

Enables your agent to assess a project's readiness for AI and generate a report. It's useful for understanding how well a project is prepared to use AI tools.

What it does

This tool assesses how ready a code repository is for artificial intelligence (AI). It generates an HTML report showing the overall score, strengths, weaknesses, and suggests actions for improvement.

When to use it

  • ✓When you want to know the AI 'health' of your project.
  • ✓To get a detailed report on how to improve your code for AI.
  • ✓To compare AI readiness between different projects.

Example of what to ask your AI

“Assess the AI readiness of this repository and create a report.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/github/awesome-copilot/blob/main/skills/acreadiness-assess/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/github/awesome-copilot/blob/main/skills/acreadiness-assess/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool runs a check on your code using a tool called AgentRC. It then uses a template to turn the results into an easy-to-understand visual report, saved as an HTML file.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add github/awesome-copilot --skill acreadiness-assess

Or download just the file:

curl -L https://raw.githubusercontent.com/github/awesome-copilot/main/skills/acreadiness-assess/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

/acreadiness-assess — AI-readiness assessment

Use this skill whenever the user asks for an AI-readiness assessment, a readiness check, an audit, or wants to see how AI-ready their repository is.

This skill is the Measure step in AgentRC's Measure → Generate → Maintain loop. The result is a self-contained HTML dashboard the user can open with file:// or commit to the repo.

Steps

  1. Confirm prerequisites. Node 20+ must be on PATH. If unsure, run node --version.

  2. Decide on a policy (optional but encouraged):

    • If the user provided --policy <source>, capture it.
    • Otherwise check agentrc.config.json for a policies array.
    • If neither, run with no policy (built-in defaults).
    • For a primer on policies, suggest the acreadiness-policy skill.
  3. Run the readiness scan in the repo root with structured output:

    npx -y github:microsoft/agentrc readiness --json [--policy <source>] [--per-area]
    

    The CommandResult<T> JSON envelope is your input for the next step.

  4. Hand off to the ai-readiness-reporter custom agent to interpret the JSON and produce reports/index.html. The agent renders via the bundled template report-template.html (shipped alongside this skill) so every report has an identical look & feel. The agent:

    • Reads the bundled report-template.html and substitutes placeholders with real data.
    • Inlines all CSS, ships a single static file (works under file://).
    • Renders maturity level, overall score, grade, pass-rate vs threshold.
    • Breaks down all 9 pillars across Repo Health (8) and AI Setup (1) with what it measures, why it matters for AI, current state, and a specific recommendation.
    • Tags every pillar with an AI relevance badge (High / Medium / Low).
    • Surfaces Extras separately (they never affect the score).
    • Shows the Active Policy including any disabled/overridden criteria and thresholds.
    • Produces a Prioritised Remediation Plan (🔴 Fix First / 🟡 Fix Next / 🔵 Plan).
    • Embeds the raw AgentRC JSON for reuse.
  5. Tell the user where the report lives (reports/index.html) and how to open it. Summarise in chat: maturity level, overall score, top three lowest pillars, and the single highest-leverage next action (almost always: run the acreadiness-generate-instructions skill).

Notes

  • AgentRC also has a built-in HTML renderer (--visual / --output report.html) but its output is intentionally generic. This skill produces a tailored, opinionated dashboard via the custom agent — closer to a code review than a metrics dump.
  • For CI gating, recommend agentrc readiness --fail-level <n> (1–5).
  • The skill never modifies repository files other than creating reports/index.html.
FAQ

What is 'AI readiness'?

It's how well your code and its organization are suited to be used or understood by AI tools, like coding assistants.

Do I need to install anything?

The tool requires you to have Node.js version 20 or higher installed on your computer.

Can I set my own rules for the assessment?

Yes, you can use custom policies to define how the scoring is calculated, focusing on specific aspects that are important to you or your organization.

Details

Original description by the author

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.

repo: github/awesome-copilot

Popularity

GitHub stars
40k
Ranking position
#4978
License
MIT
Updated
10/15/2026

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