
AI Readiness Assessment
OfficialFreeEvaluate your repository's AI readiness with a detailed report.
Free · Opens the source repo
What AI Readiness Assessment does
The AI Readiness Assessment skill enables developers to evaluate the AI readiness of their repositories effectively. By running the AgentRC readiness assessment, this skill generates a comprehensive HTML dashboard that highlights the repository's strengths and weaknesses regarding AI integration. It wraps the npx github:microsoft/agentrc readiness command and utilizes a custom agent for rendering, ensuring that the output is tailored and relevant to the user's needs.
To use this skill, users must have Node.js version 20 or higher installed. The assessment process begins with confirming prerequisites and optionally selecting an organization-specific policy for scoring. The skill then executes a readiness scan in the repository's root directory, producing structured JSON output that is interpreted by the ai-readiness-reporter agent. This agent generates a static HTML report that includes detailed metrics on various aspects of the repository's AI readiness, including maturity levels, overall scores, and specific recommendations for improvement.
The resulting dashboard is not only visually cohesive but also informative, breaking down the assessment into nine key pillars that cover both Repo Health and AI Setup. Each pillar is tagged with an AI relevance badge, providing clarity on where improvements are necessary. Additionally, the report includes a prioritized remediation plan, making it easier for developers to focus on the most critical areas for enhancement. This skill is particularly useful for teams looking to audit their repositories and ensure they are prepared for AI integration.
When to use it
Use this skill when you need to assess, audit, or score the AI readiness of a code repository.
When not to use it
This skill is not suitable for real-time monitoring or continuous integration without additional setup for CI gating.
What you can build with it
Assessing Repository for AI Integration
Use this skill when you want to evaluate how ready your repository is for AI features.
Creating an Audit Report for Stakeholders
Generate a detailed report to present to your team or stakeholders about the AI readiness of your project.
Improving Repository Health
Identify areas of improvement in your codebase by analyzing the AI readiness metrics provided in the report.
How to install AI Readiness Assessment
View source1. Install with the skills CLI
npx skills add github/awesome-copilot/acreadiness-assess --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by github/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.
Frequently asked questions about AI Readiness Assessment
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