Acreadiness Assess

GitHubOfficialFirst committed by mvanderbend-msoftDistributed by GitHub

Skill
Content generator
Software development
MIT
Low risk

From 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.

— the description by mvanderbend-msoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The acreadiness-assess skill evaluates a repository's AI readiness by running a structured scan and producing a comprehensive, static HTML dashboard. It functions as the measurement component of the AgentRC framework, providing a detailed breakdown of repository health and AI configuration across nine specific pillars. The skill interprets scan results to offer a prioritized remediation plan, maturity scoring, and actionable recommendations, delivering a report that can be viewed locally or committed to version control.

What it does

Executes an AI readiness scan on the current repository.
Generates a self-contained HTML dashboard at reports/index.html.
Provides a prioritized remediation plan categorized by urgency.
Evaluates repository health and AI setup across nine distinct pillars.
Supports custom organizational policies for tailored scoring.
Summarizes key maturity metrics and top-priority actions directly in the chat.

When to use it

When you need to audit a repository for AI readiness.
When you want to score a codebase against specific AI-readiness criteria.
When you need a visual report to share findings on repository health.
When you are preparing a repository for AI agent integration.

Advantages

Produces a portable, single-file HTML report that works without a server.
Provides clear, actionable recommendations for improving AI readiness.
Allows for policy-based customization to match organizational standards.
Integrates seamlessly into the AgentRC workflow for measurement and reporting.

Usage examples

“Assess the AI readiness of this repository.”: The agent runs the readiness scan, generates the HTML dashboard, and provides a summary of the maturity score and top remediation tasks.
“Run a readiness audit using the strict policy.”: The agent executes the scan with the specified policy file and produces a report highlighting areas that fail to meet strict criteria.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/github/acreadiness-assess/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip acreadiness-assess.zip -d .agents/skills

Documentation by mvanderbend-msoft

/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.json for a policies array.
- If neither, run with no policy (built-in defaults).
- For a primer on policies, suggest the acreadiness-policy skill.
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-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.
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.

Files

ATTRIBUTION.mdAdded by AutoGineer887 B
LICENSELicence file added by AutoGineer1.0 KiB
SKILL.md3.3 KiB
report-template.html11.6 KiB

report-template.html

<!--
  AI Readiness Report — canonical template
  --------------------------------------------
  This file is the single source of truth for the look & feel of the
  reports/index.html output. The @ai-readiness-reporter agent MUST load
  this file, substitute the {{placeholders}} with real data from
  `agentrc readiness --json`, and write the result to reports/index.html.

  Rules for the agent:
  - Do NOT change the HTML structure, class names, CSS variables or the
    inline <style> block. The template is intentionally fixed so every
    consumer of this plugin gets an identical-looking report.
  - Replace every {{placeholder}} with concrete data. Repeat the marked
    blocks (pillar cards, plan rows, maturity rows, extra rows) for
    each item. Remove blocks that don't apply (e.g. policy section if
    no policy is active).
  - Keep the file self-contained: no external CSS/JS, no network fonts.
  - Preserve the <script type="application/json" id="raw-data"> block
    and embed the compact AgentRC JSON inside it.

  Placeholders used:
    {{repoName}}       repository name
    {{date}}           ISO date the report was generated
    {{level}}          maturity level number (1-5)
    {{levelName}}      maturity level name (Functional, Documented, ...)
    {{overallPct}}     overall readiness as integer percent
    {{grade}}          letter grade A-F
    {{passRatePct}}    pass rate as integer percent (or "—" if N/A)
    {{thresholdPct}}   policy pass-rate threshold (or "—")
    {{policyName}}     active policy name (omit policy section if none)
    {{policySummary}}  one-paragraph summary of disabled/overridden criteria
    {{rawJsonCompact}} compact JSON for embedding
    {{rawJsonPretty}}  pretty JSON for the <details> view

  Pillar card placeholders (repeat per pillar):
    {{pillarName}} {{pillarScore}} {{pillarRelevance}} (high|medium|low)
    {{pillarStatus}} (good|warn|bad — drives bar + dot colour)
    {{pillarWhat}} {{pillarWhyAi}} {{pillarCurrent}} {{pillarRecommendation}}
-->
<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8" />
  <meta name="viewport" content="width=device-width, initial-scale=1" />
  <title>AI Readiness — {{repoName}}</title>
  <style>
    :root {
      --bg:#0f1115; --panel:#161a22; --panel-2:#1d2230; --border:#262c3a;
      --text:#e6e9ef; --muted:#8a93a6; --accent:#6ea8ff;
      --good:#4ade80; --warn:#fbbf24; --bad:#f87171;
    }
    * { box-sizing: border-box; }
    html,body { margin:0; background:var(--bg); color:var(--text);
      font:14px/1.5 -apple-system,BlinkMacSystemFont,"Segoe UI",Roboto,sans-serif; }
    a { color: var(--accent); }
    header { padding: 28px 32px; border-bottom: 1px solid var(--border);
      background: linear-gradient(180deg,#141823,#0f1115); }
    header h1 { margin: 0 0 4px; font-size: 22px; }
    header .meta { color: var(--muted); font-size: 13px; }
    main { max-width: 1180px; margin: 0 auto; padding: 24px 32px 80px; }
    .panel { background:var(--panel); border:1px solid var(--border);
      border-radius:10px; padding:20px; margin-bottom:18px; }
    .grid { display:grid; gap:16px; }
    .grid.cols-3 { grid-template-columns: repeat(3, 1fr); }
    .grid.cols-2 { grid-template-columns: 1fr 1fr; }
    .kpi .num { font-size: 30px; font-weight: 700; }
    .kpi .lbl { color: var(--muted); font-size: 11px; text-transform: uppercase; letter-spacing: .8px; }
    .badge { display:inline-block; padding:3px 10px; border-radius:999px;
      font-size:12px; font-weight:600; }
    .lvl-1 { background:#3a1f24; color:#f87171; }
    .lvl-2 { background:#3b2c1d; color:#fbbf24; }
    .lvl-3 { background:#2c3119; color:#d3e85e; }
    .lvl-4 { background:#1d3325; color:#4ade80; }
    .lvl-5 { background:#1c2c3d; color:#6ea8ff; }
    .bar { height:8px; background:var(--panel-2); border-radius:4px; overflow:hidden; }
    .bar > span { display:block; height:100%; background: var(--accent); }
    .bar.good > span { background: var(--good); }
    .bar.warn > span { background: var(--warn); }
    .bar.bad  > span { background: var(--bad); }
    table { width:100%; border-collapse:collapse; }
    th,td { text-align:left; padding:8px 10px; border-bottom:1px solid var(--border); font-size:13px; }
    th { color:var(--muted); font-weight:500; text-transform:uppercase; font-size:11px; letter-spacing:.8px; }
    code { background:#0a0c11; padding:1px 6px; border-radius:4px; }
    h2 { font-size:14px; color:var(--muted); text-transform:uppercase; letter-spacing:.8px; margin:0 0 12px; }
    .dot { width:8px; height:8px; border-radius:50%; display:inline-block; }
    .dot.good { background:var(--good); } .dot.warn { background:var(--warn); } .dot.bad { background:var(--bad); }
    footer { color: var(--muted); font-size: 12px; text-align: center; padding: 20px; }

    /* Pillar cards */
    .pillar { background:var(--panel-2); border:1px solid var(--border);
      border-radius:8px; padding:14px 16px; }
    .pillar h3 { margin:0 0 6px; font-size:15px; display:flex; align-items:center; gap:10px; flex-wrap:wrap; }
    .pillar .why  { color:var(--muted); font-size:13px; margin:8px 0 0; }
    .pillar .what { font-size:13px; margin:6px 0 0; }
    .pillar .rec  { font-size:13px; margin:8px 0 0; }
    .rel { font-size:10px; padding:2px 8px; border-radius:999px; text-transform:uppercase; letter-spacing:.6px; font-weight:600; }
    .rel.high   { background:#1c2c3d; color:#6ea8ff; }
    .rel.medium { background:#2c3119; color:#d3e85e; }
    .rel.low    { background:#262c3a; color:#8a93a6; }
  </style>
</head>
<body>
  <header>
    <h1>AI Readiness Report</h1>
    <div class="meta">
      <strong>{{repoName}}</strong> · Assessed {{date}} ·
      <span class="badge lvl-{{level}}">L{{level}} — {{levelName}}</span> ·
      Overall <strong>{{overallPct}}%</strong> · Grade <strong>{{grade}}</strong>
      <!-- if a policy is active, append: · Policy <code>{{policyName}}</code> -->
    </div>
  </header>

  <main>

    <!-- 1. What is AI Readiness? -->
    <section class="panel">
      <h2>What is AI Readiness?</h2>
      <p>AI coding agents are only as effective as the context they receive. AgentRC measures how AI-ready a repo is across <strong>9 pillars</strong> in two categories — Repo Health and AI Setup — and maps the result to a <strong>5-level maturity model</strong>. This report is the <em>Measure</em> step in AgentRC's <em>Measure → Generate → Maintain</em> loop.</p>
      <p style="color:var(--muted);font-size:13px;margin-top:8px">Each pillar carries an <strong>AI relevance</strong> rating (High / Medium / Low) so you can tell at a glance which gaps most directly affect Copilot's output and which are general engineering hygiene.</p>
    </section>

    <!-- 2. KPIs -->
    <section class="grid cols-3">
      <div class="panel kpi"><span class="lbl">Maturity</span><div class="num"><span class="badge lvl-{{level}}">L{{level}} — {{levelName}}</span></div></div>
      <div class="panel kpi"><span class="lbl">Overall Score</span><div class="num">{{overallPct}}%</div><div style="color:var(--muted);font-size:12px">Grade {{grade}}</div></div>
      <div class="panel kpi"><span class="lbl">Pass rate</span><div class="num">{{passRate}}</div><div style="color:var(--muted);font-size:12px">Threshold {{threshold}}</div></div>
    </section>

    <!-- 3. Maturity progression -->
    <section class="panel">
      <h2>Maturity Progression</h2>
      <table>
        <thead><tr><th>Level</th><th>Name</th><th>Status</th></tr></thead>
        <tbody>
          <!-- Render levels 5 → 1. Mark the current level with "◼ You are here". Example row:
            <tr><td>L3</td><td>Standardized</td><td>◼ You are here</td></tr>
          -->
        </tbody>
      </table>
    </section>

    <!-- 4. Active policy (omit this section entirely when no policy is active) -->
    <section class="panel">
      <h2>Active Policy</h2>
      <p><code>{{policyName}}</code> — {{policySummary}}</p>
    </section>

    <!-- 5. Repo Health Pillars -->
    <section class="panel">
      <h2>Repo Health Breakdown</h2>
      <div class="grid cols-2">
        <!--
          Repeat one .pillar block per Repo Health pillar (8 pillars):
          Style, Build, Testing, Docs, Dev Environment, Code Quality, Observability, Security.

          <div class="pillar">
            <h3>
              <span class="dot {{pillarStatus}}"></span>
              {{pillarName}}
              <span class="rel {{pillarRelevance}}">AI relevance: {{pillarRelevance}}</span>
              <span style="margin-left:auto;color:var(--muted);font-size:13px">{{pillarScore}}%</span>
            </h3>
            <div class="bar {{pillarStatus}}"><span style="width:{{pillarScore}}%"></span></div>
            <p class="what"><strong>What it measures:</strong> {{pillarWhat}}</p>
            <p class="why"><strong>Why it matters for AI:</strong> {{pillarWhyAi}}</p>
            <p class="rec"><strong>Current state:</strong> {{pillarCurrent}}</p>
            <p class="rec"><strong>Recommendation:</strong> {{pillarRecommendation}}</p>
          </div>
        -->
      </div>
    </section>

    <!-- 6. AI Setup Pillars -->
    <section class="panel">
      <h2>AI Setup Breakdown</h2>
      <div class="grid cols-2">
        <!-- AI Tooling pillar block — same structure as above, AI relevance is always "high". -->
      </div>
    </section>

    <!-- 7. Extras -->
    <section class="panel">
      <h2>Extras (informational, do not affect score)</h2>
      <table>
        <thead><tr><th></th><th>Extra</th><th>Status</th></tr></thead>
        <tbody>
          <!-- agents-doc, pr-template, pre-commit, architecture-doc rows. Use ✅ or ◻. -->
        </tbody>
      </table>
    </section>

    <!-- 8. Prioritised Remediation Plan -->
    <section class="panel">
      <h2>Prioritised Remediation Plan</h2>
      <h3 style="color:var(--bad)">🔴 Fix First (high impact / low effort)</h3>
      <table><thead><tr><th>#</th><th>Finding</th><th>File / config</th><th>Why it matters</th></tr></thead><tbody><!-- rows --></tbody></table>
      <h3 style="color:var(--warn)">🟡 Fix Next (medium impact / low effort)</h3>
      <table><thead><tr><th>#</th><th>Finding</th><th>File / config</th><th>Why</th></tr></thead><tbody><!-- rows --></tbody></table>
      <h3 style="color:var(--accent)">🔵 Plan (medium impact / medium effort)</h3>
      <table><thead><tr><th>#</th><th>Finding</th><th>File / config</th><th>Why</th></tr></thead><tbody><!-- rows --></tbody></table>
    </section>

    <!-- 9. Next steps -->
    <section class="panel">
      <h2>Next Steps</h2>
      <ol>
        <li>Generate or refresh instructions: <code>agentrc instructions --output .github/copilot-instructions.md</code> (or use the <code>generate-instructions</code> skill).</li>
        <li>Address each item under <strong>🔴 Fix First</strong>; re-run this report to confirm score improvement.</li>
        <li>Codify org standards via a JSON policy (<code>strict.json</code>, <code>ai-only.json</code>, …) and re-run with <code>--policy</code>.</li>
        <li>Wire <code>agentrc readiness --fail-level &lt;n&gt;</code> into CI to prevent regressions.</li>
      </ol>
    </section>

    <!-- 10. Raw data -->
    <details class="panel">
      <summary style="cursor:pointer;color:var(--muted)">Raw AgentRC JSON</summary>
      <pre style="overflow:auto;font-size:11px;color:#b8c0d2">{{rawJsonPretty}}</pre>
    </details>
    <script type="application/json" id="raw-data">{{rawJsonCompact}}</script>
  </main>

  <footer>
    Generated by <a href="https://github.com/github/awesome-copilot/tree/main/plugins/acreadiness-cockpit">acreadiness-cockpit</a>
    · powered by <a href="https://github.com/microsoft/agentrc">microsoft/agentrc</a>.
  </footer>
</body>
</html>

Requirements and compatibility

Written for: GitHub Copilot, Claude Code

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Claude Code frontmatter, Needs Node.js