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acreadiness-assess

★ 35K repomlN/AIntermediateClaude
🤖 AI Summary

This skill runs an AI-readiness audit on a repository, producing a self-contained HTML dashboard. It checks for Node 20+, optionally applies a policy from `--policy` or `agentrc.config.json`, and executes the "Measure" step of the Measure → Generate → Maintain loop.

How to Install

Claude Code:
git clone --depth 1 https://github.com/github/awesome-copilot.git && cp awesome-copilot/skills/acreadiness-assess ~/.claude/skills/acreadiness-assess -r
# /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 `, 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: ```bash npx -y github:microsoft/agentrc readiness --json [--policy ] [--per-area] ``` The `CommandResult` 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 ` (1–5). - The skill never modifies repository files other than creating `reports/index.html`.

Details

Category AI/ML → ml
Sourcegithub/awesome-copilot
SKILL.mdView on GitHub →
Repo Stars★ 35.6K
Est. per Skill712 (shared across 50 skills from this repo)
DifficultyIntermediate
Risk LevelN/A

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