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acreadiness-assess skill

by github·github/awesome-copilot·39k stars·MIT

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.

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Install the acreadiness-assess skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description. 

git clone --depth 1 https://github.com/github/awesome-copilot.git /tmp/awesome-copilot
mkdir -p ~/.claude/skills
cp -r /tmp/awesome-copilot/skills/acreadiness-assess ~/.claude/skills/acreadiness-assess
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on 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.
  1. Decide on a policy (optional but encouraged):
  • If the user provided --policy , 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.
  1. Run the readiness scan in the repo root with structured output:
npx -y github:microsoft/agentrc readiness --json [--policy <source>] [--per-area]

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

  1. 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.
  1. 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 (1–5).
  • The skill never modifies repository files other than creating reports/index.html.

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