Official agent skill

Agent Readiness Audit

by docker in docker/docs

Audit a documentation site for agent-friendliness: discovery, markdown delivery, crawlability, semantic structure, machine-readable surfaces, and content legibility.

OfficialApache-2.0Auto-check passedFrontend & Design

Install Agent Readiness Audit

skills CLI
$ npx skills add docker/docs --skill agent-readiness-audit -a claude-code

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

GitHub CLI
$ gh skill install docker/docs agent-readiness-audit --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/docker/docs.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/agent-readiness-audit .claude/skills/agent-readiness-audit && 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
agent-readiness-audit
GitHub stars
4.7k
Token cost
~1.8k tokens
SKILL.md length
939 words
Files
4 (incl. scripts, references)
Skills in repo
13
Repo updated
First seen
Licence
Apache-2.0

At a glance

Audit a documentation site for agent-friendliness: discovery, markdown delivery, crawlability, semantic structure, machine-readable surfaces, and content legibility.

  • Works in 9 steps: Set scope → Gather sitewide signals → Sample representative pages → …
  • Asked to assess docs.docker.com
  • SKILL.md covers 1. Set scope, 2. Gather sitewide signals, 3. Sample representative pages and 4. Run fetch-path checks on…, plus 6 more sections
  • Runs Shell scripts from its folder; calls bash

What it does

Agent Readiness Audit is an agent skill from docker/docs, published by the product's own GitHub organization. Audit a documentation site for agent-friendliness: discovery, markdown delivery, crawlability, semantic structure, machine-readable surfaces, and content legibility. Use when asked to assess docs.docker.com or any docs site for AI/agent readiness, produce a scored report, compare with external scanners, or generate a remediation list. Triggers on: "audit docs for agent readiness", "how agent-friendly is docs.docker.com", "score our docs for AI agents", "review llms.txt / markdown / crawlability", "create an…

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/report-template.md`, `references/rubric.md` and `scripts/baseline-probes.sh`).

It sits in Frontend & Design, covering Static sites and blogs, Technical SEO and AI search optimization. It works with Docker and Model Context Protocol. The repository describes itself as: Source repo for Docker's Documentation. The licence is Apache-2.0.

When your agent uses it

  • Asked to assess docs.docker.com
  • Any docs site for AI/agent readiness
  • Produce a scored report
  • Compare with external scanners

Example prompts

  • “audit docs for agent readiness”
  • “how agent-friendly is docs.docker.com”
  • “score our docs for AI agents”
  • “/agent-readiness-audit”

Requirements

  • A Bash shell
  • Docker

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Set scope
  2. Gather sitewide signals
  3. Sample representative pages
  4. Run fetch-path checks on each sample
  5. Judge structure and legibility
  6. Score with the rubric
  7. Compare with external scanners when useful
  8. Produce a remediation list
  9. Report in a stable format

What it can do on your machine

Read from SKILL.md and the folder at commit 65aa5cd. 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

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • bash

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

  • Network

    No URLs in SKILL.md.

    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

Agent Readiness Audit loads about 1.8k tokens when it runs, and up to ~3.5k if it reads all its reference files. Until then it costs about 142 tokens; SKILL.md has 939 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~142
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.5k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from docker/docs at commit 65aa5cd, republished under its Apache-2.0 licence (© docker). 939 words, ~1,820 tokens.

Download SKILL.mdSave it as .claude/skills/agent-readiness-audit/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
agent-readiness-audit
description
Audit a documentation site for agent-friendliness: discovery, markdown delivery, crawlability, semantic structure, machine-readable surfaces, and content legibility. Use when asked to assess docs.docker.com or any docs site for AI/agent readiness, produce a scored report, compare with external scanners, or generate a remediation list. Triggers on: "audit docs for agent readiness", "how agent-friendly is docs.docker.com", "score our docs for AI agents", "review llms.txt / markdown / crawlability", "create an agent-readiness remediation plan".
argument-hint
<base-url>

Agent Readiness Audit

Audit the live site, not the source tree alone. Prefer the same fetch path an external agent would use in the wild: direct HTTP requests, sitemap sampling, and page-level inspection.

Do not reduce the result to a homepage-only scan or a binary checklist.

1. Set scope

Use $ARGUMENTS as the base URL when provided. Otherwise infer the base URL from context and state the assumption.

Decide whether the host being audited is:

  • a docs-only host
  • an app/tool host
  • a mixed host

This matters for optional checks such as MCP, plugin manifests, or other tool discovery files. Do not penalize a docs-only host for missing tooling manifests that belong on a separate service.

For docs.docker.com, treat the public docs host as docs-only. Docker's MCP server is published separately, so missing MCP files on the docs host should be reported as N/A, not as a failure.

2. Gather sitewide signals

Always check these resources first:

  • /llms.txt
  • /llms-full.txt
  • /robots.txt
  • /sitemap.xml

Only check host-level tool manifests when the host is an app/tool host, mixed host, or explicitly advertises them:

  • /.well-known/ai-plugin.json
  • /.well-known/agent.json
  • /.well-known/agents.json

Use the bundled script for a baseline:

bash
bash .agents/skills/agent-readiness-audit/scripts/baseline-probes.sh \
  "$ARGUMENTS"

The script produces baseline evidence only. You still need to interpret what matters for a docs property and score it with the rubric.

For docs-only hosts, you may skip tool-manifest probes to reduce noise:

bash
CHECK_TOOL_MANIFESTS=0 \
  bash .agents/skills/agent-readiness-audit/scripts/baseline-probes.sh \
  "$ARGUMENTS"

3. Sample representative pages

Use the sitemap when available. Do not rely on the homepage alone.

If llms.txt exists, sample some URLs from it as well. This helps catch stale or misleading discovery surfaces that a sitemap-only sample would miss.

Sample at least 12 pages when the site is large enough, and cover multiple page types:

  • homepage or docs landing page
  • section landing pages
  • task guides
  • product manuals
  • reference or API pages
  • tutorial or learning pages

If the sitemap is missing or unusable, discover pages through internal links and note the lower confidence.

If the site has distinct delivery patterns, sample each one. For example:

  • normal content pages
  • generated reference pages
  • versioned docs
  • localized docs

4. Run fetch-path checks on each sample

For each sampled page, verify:

  • HTML fetch status, content type, and final URL
  • Accept: text/markdown behavior
  • direct markdown route behavior such as <page>.md or another stable path
  • page-level markdown alternate links and whether they actually resolve
  • whether page actions such as "Open Markdown" agree with the working route
  • whether the HTML title or H1 matches the markdown H1 closely enough for retrieval parity
  • whether main content is present in the initial HTML
  • redirect chain length and canonical URL consistency
  • obvious chrome/noise in the markdown response

Do not assume a .md mirror exists just because another site uses one. Verify the actual markdown path the site exposes.

Treat these as separate signals:

  • negotiated markdown works
  • a stable direct markdown URL works
  • the page advertises the correct markdown URL

If the page advertises dead markdown alternates but a working markdown route exists, do not fail markdown delivery outright. Score it as a discoverability and consistency problem instead.

For API or generated reference pages, also verify whether a machine-readable asset such as OpenAPI YAML is directly linked and fetchable.

Show full SKILL.md (419 more words)Show less

5. Judge structure and legibility

Measure structural signals:

  • exactly one h1
  • sane heading hierarchy
  • main and article presence where appropriate
  • canonical tags
  • JSON-LD or breadcrumb structured data
  • stable anchors and deep-linkable headings

Also make a qualitative judgment about agent legibility:

  • markdown strips site chrome cleanly
  • headings are specific and task-oriented
  • code blocks stay intelligible without client-side JS
  • the page is not dominated by banners, injected chat, or nav noise

Measure code block labeling explicitly when code samples are common. A page type with many untagged fenced blocks should lose points even if the prose is otherwise clean.

For page types that intentionally render interactive UIs with JavaScript, judge them separately from normal docs pages. If the HTML shell is thin, check whether the page still provides:

  • a fetchable markdown summary
  • a directly linked machine-readable asset
  • a usable non-JS fallback

6. Score with the rubric

Use references/rubric.md.

Rules:

  • score only what you verified
  • mark non-applicable checks as N/A
  • normalize the final score against applicable points only
  • do not let optional manifest checks dominate the grade

Apply the foundational caps from the rubric. A site with broken discovery or broken markdown delivery should not earn a high grade because it has clean metadata.

Do not average away a weak page type. If one major page type, such as API reference, is materially worse than the rest of the corpus, call it out as the weakest segment and reflect it in the category notes.

7. Compare with external scanners when useful

If external scanner results are available, compare them to your live findings. Treat them as secondary evidence.

If a scanner and the live fetch disagree:

  • trust the live fetch
  • report the mismatch explicitly
  • explain whether the scanner is testing a different assumption

8. Produce a remediation list

Turn findings into a short backlog:

  • P0: fetchability or discovery blockers
  • P1: recurring structural or parity issues
  • P2: polish, optional manifests, or low-impact enhancements

For each remediation, include:

  • the failing signal
  • why it matters to agents
  • a concrete fix
  • whether it is sitewide or page-type-specific

9. Report in a stable format

Use references/report-template.md.

Always include:

  • overall score and grade
  • confidence level
  • sampled URLs or sample strategy
  • category scores
  • highest-priority findings
  • remediation backlog

Notes

  • Favor docs-delivery checks over marketing-site heuristics.
  • Do not fail a docs host for lacking MCP or plugin manifests unless the host itself is meant to expose tools.
  • Treat raw byte size as supporting evidence, not as a primary scoring input.
  • Prefer short evidence excerpts and commands over long copied page text.

© docker, Apache-2.0. 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 3 other files (scripts, references) in .agents/skills/agent-readiness-audit of docker/docs.

  • SKILL.md
  • references/report-template.md
  • references/rubric.md
  • scripts/baseline-probes.sh

Open the folder on GitHubat commit 65aa5cd

Compare with similar skills

Agent Readiness Audit 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.

Agent Readiness Audit compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Agent Readiness Audit this skilldocker/docs4.7k—~1.8kAutomated safety check: PassApache-2.0
Frontend Build Timing Auditopenops-cloud/openops1.1k—~2.3kAutomated safety check: PassCustom licence
Create Docsvictorgarciaesgi/nuxt-typed-router4132 repos~2.8kAutomated safety check: PassMIT
Oneclickvirtoneclickvirt/oneclickvirt372—~1.1kAutomated safety check: PassGPL-3.0
Cognee Docker Setuptopoteretes/cognee32k1 repos~901Automated safety check: NotesApache-2.0
Unraiddinglebear-ai/unraid135—~5.4kAutomated safety check: NotesMIT

Similar skills

  • Frontend Build Timing Audit

    openops-cloud/openops

    Detects and diagnoses chunk-evaluation timing bugs in the Vite/rolldown production build of react-ui (works-in-dev / broken-in-build i18n regressions, missing UI labels, module-scope t()…

    1.1k GitHub stars~2.3k tokensUpdated yesterday
    Frontend & DesignAuto-check passed
  • Create Docs

    victorgarciaesgi/nuxt-typed-router

    Create complete documentation sites for projects. An agent skill from victorgarciaesgi/nuxt-typed-router.

    413 GitHub starsUsed in 2 repos~2.8k tokens
    Frontend & DesignAuto-check passed
  • Oneclickvirt

    oneclickvirt/oneclickvirt

    OneClickVirt operations skill for managing containers, virtual machines, provider nodes, health checks, and metrics through MCP.

    372 GitHub stars~1.1k tokensUpdated 5 days ago
    DevOps & CloudAuto-check passed
  • Cognee Docker Setup

    topoteretes/cognee

    Runs the Cognee AI memory platform in Docker, from a one-file prebuilt image to a full compose stack with UI, MCP server, Postgres and Neo4j.

    32k GitHub starsUsed in 1 repo~901 tokens
    DevOps & CloudAuto-check: notes
  • Unraid

    dinglebear-ai/unraid

    This skill should be used when the user mentions Unraid, asks to check server health, monitor array or disk status, list or restart Docker containers, start or stop VMs, read system logs, check…

    135 GitHub stars~5.4k tokensUpdated 3 days ago
    DevOps & CloudAuto-check: notes
  • Devsy

    devsy-org/devsy

    Operate Devsy workspaces and providers for end users. An agent skill from devsy-org/devsy.

    109 GitHub stars~1.7k tokensUpdated today
    DevOps & CloudAuto-check passed

More from docker/docs

All 13 skills in this repo
  • Official

    Handle Hugo docs information-architecture moves: discover old vs new URLs, add front matter aliases (Phase 1), update in-repo links (Phase 2), interactive List 2 resolution and fragment validation…

    4.7k GitHub stars~5.1k tokensUpdated today
    Auto-check passed
  • Write

    docker/docs

    Official

    Write or edit reader-facing technical prose for immediate comprehension.

    4.7k GitHub stars~1.1k tokensUpdated today
    Auto-check passed
  • Create Lab Guide

    docker/docs

    Official

    Clone a dockersamples Labspace repo, extract learning objectives and module structure from labspace.yaml, and produce a Hugo guide page under content/guides/ with correct frontmatter…

    4.7k GitHub stars~1k tokensUpdated today
    Auto-check passed
  • Curate Whats New

    docker/docs

    Official

    Curate noteworthy Docker launches from documentation pull requests merged during a requested period.

    4.7k GitHub stars~1.3k tokensUpdated today
    Auto-check passed
  • Fix Issue

    docker/docs

    Official

    Fix a single GitHub issue end-to-end: triage, research, write the fix, review, and create a PR.

    4.7k GitHub stars~595 tokensUpdated today
    Auto-check passed
  • Maintain PR

    docker/docs

    Official

    Maintain and follow up on a single Docker documentation pull request that you own or are responsible for updating.

    4.7k GitHub stars~825 tokensUpdated today
    Auto-check passed

Questions about Agent Readiness Audit

What does Agent Readiness Audit do?

Audit a documentation site for agent-friendliness: discovery, markdown delivery, crawlability, semantic structure, machine-readable surfaces, and content legibility. Agent Readiness Audit is an agent skill from docker/docs, published by the product's own GitHub organization. Audit a documentation site for agent-friendliness: discovery, markdown delivery, crawlability, semantic structure, machine-readable surfaces, and content legibility.

When should I use Agent Readiness Audit?

Agent Readiness Audit fits situations like: asked to assess docs.docker.com; any docs site for AI/agent readiness; produce a scored report; compare with external scanners.

How do I install Agent Readiness Audit in Claude Code?

Run `npx skills add docker/docs --skill agent-readiness-audit -a claude-code`. Or copy the skill folder (.agents/skills/agent-readiness-audit in docker/docs) into .claude/skills/agent-readiness-audit in your project. Claude Code loads it when a task matches its description.

How do I install Agent Readiness Audit in Codex?

Run `npx skills add docker/docs --skill agent-readiness-audit -a codex`. Or copy the skill folder (.agents/skills/agent-readiness-audit in docker/docs) into .agents/skills/agent-readiness-audit in your project. Codex loads it when a task matches its description.

Can I use Agent Readiness Audit 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 docker/docs --skill agent-readiness-audit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-readiness-audit, .gemini/skills/agent-readiness-audit, .github/skills/agent-readiness-audit and .opencode/skills/agent-readiness-audit in your project.

What does Agent Readiness Audit need to run?

Going by SKILL.md and its folder, Agent Readiness Audit needs a shell for the scripts in its folder and the command-line tools its instructions call (bash). Our summary lists: A Bash shell; Docker.

Does Agent Readiness Audit access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Agent Readiness Audit 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Agent Readiness Audit use?

Agent Readiness Audit is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agent Readiness Audit use?

About 1.8k tokens (SKILL.md is roughly 7.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.7k tokens, read only when the agent opens those files.

What are the alternatives to Agent Readiness Audit?

Skills that share tags, products or a category with Agent Readiness Audit: Frontend Build Timing Audit (openops-cloud/openops, 1.1k stars), Create Docs (victorgarciaesgi/nuxt-typed-router, 413 stars), Oneclickvirt (oneclickvirt/oneclickvirt, 372 stars) and Cognee Docker Setup (topoteretes/cognee, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agent Readiness Audit?

docker (a GitHub organization, an official publisher) maintains it in docker/docs, which has 4,666 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on October 7, 2026.

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