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github/acreadiness-assess

github

acreadiness-assess

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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v1.0Saved Jun 26, 2026

/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.
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Overall Score

88/100

Grade

A

Excellent

Safety

90

Quality

88

Clarity

86

Completeness

84

Summary

This skill runs the Microsoft AgentRC readiness assessment on a repository and produces a static HTML dashboard via a custom rendering agent. It wraps `npx github:microsoft/agentrc readiness --json`, supports org-specific policies, and outputs a self-contained report to `reports/index.html` with scoring, pillar breakdowns, and remediation guidance.

Detected Capabilities

shell execution (npx)file write (reports/index.html)file read (agentrc.config.json, policies, report-template.html)custom agent handoff (ai-readiness-reporter)JSON parsing and rendering

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

assess ai readinessmeasure repository readinessrun agentrc assessmentaudit repo ai-readinessgenerate readiness reportevaluate ai-readyai readiness dashboardcheck readiness score

Risk Signals

INFO

Outbound network request via npx to github.com/microsoft/agentrc

Step 3: npx -y github:microsoft/agentrc readiness --json
INFO

File write to reports/index.html (project-scoped)

Step 4: ai-readiness-reporter produces reports/index.html
INFO

Optional policy file read from user-provided path or agentrc.config.json

Step 2: --policy <source> or agentrc.config.json

Referenced Domains

External domains referenced in skill content, detected by static analysis.

github.com

Use Cases

  • /acreadiness-assess — measure AI-readiness of a repository at a point in time
  • Audit a repo's readiness across 9 pillars (Repo Health and AI Setup) and understand AI-readiness gaps
  • Generate a static dashboard report to share with team stakeholders (no server required)
  • Assess readiness impact of org-specific policies by providing custom policy JSON
  • Establish a baseline before running acreadiness-generate-instructions to create AI instructions

Quality Notes

  • Clear, well-structured instructions with numbered steps and explicit decision logic (Step 2 policy flow)
  • Policy parameter is optional but encouraged, with a reference to acreadiness-policy skill for further learning
  • Well-documented handoff to custom agent (@ai-readiness-reporter) with explicit rules for template substitution (preserved structure, placeholder replacement, self-contained output)
  • Report template is comprehensive: KPIs, maturity progression, pillar breakdowns, remediation plan, and raw JSON embedding all specified
  • Good boundaries: does not modify repo files except reports/index.html; clearly states 'never modifies repository files' in Notes
  • Concise summary at the end (chat output) guides user to next actions and explains the Measure→Generate→Maintain loop
  • References github.com for package source and includes MIT license
  • Includes maturity-level badge styling (lvl-1 through lvl-5) in template CSS for visual consistency
Model: claude-haiku-4-5-20251001Analyzed: Jun 26, 2026

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