Official agent skill

Acreadiness Assess

by github in github/awesome-copilot

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html.

OfficialMITAuto-check passedLegal & Compliance

Install Acreadiness Assess

skills CLI
$ npx skills add github/awesome-copilot --skill acreadiness-assess -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install github/awesome-copilot acreadiness-assess --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/acreadiness-assess .claude/skills/acreadiness-assess && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
acreadiness-assess
GitHub stars
40k
Used in
1 other repo
Token cost
~839 tokens
SKILL.md length
370 words
Files
2
Skills in repo
417
Repo updated
First seen
Licence
MIT

At a glance

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html.

  • Works in 5 steps: Confirm prerequisites. Node 20+ must be… → Decide on a policy (optional but… → Run the readiness scan in the repo root… → …
  • Asked to assess
  • SKILL.md covers Steps and Notes
  • Calls npx and node

What it does

Acreadiness Assess is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. 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.

Its SKILL.md is about 840 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file.

It sits in Legal & Compliance, covering Audit readiness. It works with GitHub. The repository describes itself as: Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot. The licence is MIT.

When your agent uses it

  • Asked to assess
  • Score the AI readiness of a repo

Example prompts

  • “/acreadiness-assess”

Requirements

  • Node.js

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Confirm prerequisites. Node 20+ must be on PATH. If unsure, run node --version.
  2. Decide on a policy (optional but encouraged)
  3. Run the readiness scan in the repo root with structured output
  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…
  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…

What it can do on your machine

Read from SKILL.md and the folder at commit 727ff2e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npx
    • node

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Acreadiness Assess loads about 839 tokens when it runs. Until then it costs about 95 tokens; SKILL.md has 370 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~95
When it runs · the whole SKILL.md, loaded when a task matches
~839

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from github/awesome-copilot at commit 727ff2e, republished under its MIT licence (© github). 370 words, ~839 tokens.

Download SKILL.mdSave it as .claude/skills/acreadiness-assess/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
acreadiness-assess
description
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.
argument-hint
[--policy <path-or-pkg>] [--per-area] — e.g. /acreadiness-assess, /acreadiness-assess --policy ./policies/strict.json

/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:

    bash
    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).

Show full SKILL.md (56 more words)Show less

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.

© github, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/acreadiness-assess of github/awesome-copilot.

  • SKILL.md
  • report-template.html

Open the folder on GitHubat commit 727ff2e

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in github/awesome-copilot, which our catalogue first saw on October 7, 2026.

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Acreadiness Assess next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Acreadiness Assess compared with similar skills
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HIPAA Safe Harbor Coverage Auditmaziyarpanahi/openmed5.5k—~1.7kAutomated safety check: PassApache-2.0
Audit Fixopenplayerjs/openplayerjs649—~1kAutomated safety check: PassMIT
ISO Standards Readiness EvidenceK-Dense-AI/scientific-agent-skills48k1 repos~4.6kAutomated safety check: NotesMIT

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Works with

Questions about Acreadiness Assess

What does Acreadiness Assess do?

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Acreadiness Assess is an agent skill from github/awesome-copilot, published by the product's own GitHub organization.html.

When should I use Acreadiness Assess?

Acreadiness Assess fits situations like: asked to assess; score the AI readiness of a repo.

How do I install Acreadiness Assess in Claude Code?

Run `npx skills add github/awesome-copilot --skill acreadiness-assess -a claude-code`. Or copy the skill folder (skills/acreadiness-assess in github/awesome-copilot) into .claude/skills/acreadiness-assess in your project. Claude Code loads it when a task matches its description.

How do I install Acreadiness Assess in Codex?

Run `npx skills add github/awesome-copilot --skill acreadiness-assess -a codex`. Or copy the skill folder (skills/acreadiness-assess in github/awesome-copilot) into .agents/skills/acreadiness-assess in your project. Codex loads it when a task matches its description.

Can I use Acreadiness Assess in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add github/awesome-copilot --skill acreadiness-assess -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/acreadiness-assess, .gemini/skills/acreadiness-assess, .github/skills/acreadiness-assess and .opencode/skills/acreadiness-assess in your project.

What does Acreadiness Assess need to run?

Going by SKILL.md and its folder, Acreadiness Assess needs the command-line tools its instructions call (npx and node). Our summary lists: Node.js.

Does Acreadiness Assess access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Acreadiness Assess safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Acreadiness Assess use?

Acreadiness Assess is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Acreadiness Assess use?

About 839 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Acreadiness Assess?

Skills that share tags, products or a category with Acreadiness Assess: Performing Soc2 Type2 Audit Preparation (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), A2ui Remediate Problem (a2ui-project/a2ui, 17k stars), HIPAA Safe Harbor Coverage Audit (maziyarpanahi/openmed, 5.5k stars) and Audit Fix (openplayerjs/openplayerjs, 649 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Acreadiness Assess?

github (a GitHub organization, an official publisher) maintains it in github/awesome-copilot, which has 39,748 GitHub stars. The repository holds 417 skills in this directory. The repository was last updated on October 7, 2026.

Source: github/awesome-copilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.