- name
- acreadiness-assess
- description
- 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.
- argument-hint
- [--policy <path-or-pkg>] [--per-area] — e.g. /acreadiness-assess, /acreadiness-assess --policy ./policies/strict.json
/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
-
Confirm prerequisites. Node 20+ must be on PATH. If unsure, run
node --version. -
Decide on a policy (optional but encouraged):
- If the user provided
--policy <source>, capture it. - Otherwise check
agentrc.config.jsonfor apoliciesarray. - If neither, run with no policy (built-in defaults).
- For a primer on policies, suggest the
acreadiness-policyskill.
- If the user provided
-
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. -
Hand off to the
ai-readiness-reportercustom agent to interpret the JSON and producereports/index.html. The agent renders via the bundled templatereport-template.html(shipped alongside this skill) so every report has an identical look & feel. The agent:- Reads the bundled
report-template.htmland 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).
- Reads the bundled