AI Readiness Assessment
Audit your repository's AI-readiness and generate an interactive HTML dashboard.
Installation
- Make sure Claude is on your device and in your terminal.
Skills load from
~/.claude/skills/when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then runclaudein any terminal to verify.One-time setupnpm i -g @anthropic-ai/claude-codeAlready have it? Skip ahead.
- Paste into Claude Code or into your terminal.
This copies the whole skill folder into
~/.claude/skills/acreadiness-assess-github/— the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.Faster alternative (instruction-only skills)
Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.
Quick install (SKILL.md only)Sign up to copy - Restart Claude Code.
Quit and reopen Claude Code (or any other agent that loads from
~/.claude/skills/). New skills are picked up on startup. - Just ask Claude.
Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.
Prefer to read the source first? Open on GitHub.
When Claude uses it
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.
What this skill does
/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).
- 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.
- Reads the bundled
-
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 theacreadiness-generate-instructionsskill).
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.
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