Agent skill

API Docs Quality Report

by Infrasity-Labs in Infrasity-Labs/dev-gtm-claude-skills

Audits any API documentation site by crawling every endpoint page and scoring each one across 5 checks: description quality, OpenAPI spec presence, body param descriptions, response codes, and…

MITAuto-check passedDevelopment

Install API Docs Quality Report

skills CLI
$ npx skills add Infrasity-Labs/dev-gtm-claude-skills --skill api-docs-quality-report -a claude-code

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

GitHub CLI
$ gh skill install Infrasity-Labs/dev-gtm-claude-skills api-docs-quality-report --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/Infrasity-Labs/dev-gtm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/api-docs-quality-report .claude/skills/api-docs-quality-report && 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
api-docs-quality-report
GitHub stars
139
Token cost
~2.5k tokens
SKILL.md length
1,159 words
Files
4 (incl. references)
Skills in repo
26
Repo updated
First seen
Licence
MIT

At a glance

Audits any API documentation site by crawling every endpoint page and scoring each one across 5 checks: description quality, OpenAPI spec presence, body param descriptions, response codes, and…

  • Works in 9 steps: COLLECT INPUT → DISCOVER ALL ENDPOINT PAGES → CHECK OPENAPI SPEC AVAILABILITY → …
  • This skill whenever a user provides a documentation URL and asks to audit
  • SKILL.md covers STEP 0 — COLLECT INPUT, STEP 1 — DISCOVER ALL ENDPOINT…, STEP 2 — CHECK OPENAPI SPEC… and STEP 3 — FETCH AND PARSE ALL…, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

API Docs Quality Report is an agent skill from Infrasity-Labs/dev-gtm-claude-skills. Audits any API documentation site by crawling every endpoint page and scoring each one across 5 checks: description quality, OpenAPI spec presence, body param descriptions, response codes, and response schema completeness. Produces a polished interactive HTML report with a summary scorecard, site-wide pattern analysis, ranked top issues, and per-endpoint findings with specific fix guidance. Trigger this skill whenever a user provides a documentation URL and asks to audit, review, analyse, or check their API docs…

Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `README.md`, `references/html-template.md` and `references/scoring-rules.md`).

It sits in Development, covering Technical documentation and OpenAPI specifications. It works with OpenAPI. The repository describes itself as: Open-source Claude skills for GEO, AI discoverability, and developer GTM workflows. Built for developer-focused companies that want their documentation to be found, parsed, and… The licence is MIT.

When your agent uses it

  • This skill whenever a user provides a documentation URL and asks to audit
  • Check their API docs
  • : do the same audit for X
  • Audit docs.company.com

Example prompts

  • “do the same audit for X”
  • “audit docs.company.com”
  • “check the API docs at X”
  • “/api-docs-quality-report”

Workflow steps

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

  1. COLLECT INPUT
  2. DISCOVER ALL ENDPOINT PAGES
  3. CHECK OPENAPI SPEC AVAILABILITY
  4. FETCH AND PARSE ALL ENDPOINT PAGES
  5. SCORE EACH ENDPOINT (5 CHECKS)
  6. DETECT SITE-WIDE PATTERNS
  7. COMPILE TOP ISSUES
  8. BUILD SCORECARD
  9. GENERATE HTML REPORT

What it can do on your machine

Read from SKILL.md and the folder at commit 02cfefb. 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

    No scripts in the folder and no shell commands in SKILL.md.

    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

API Docs Quality Report loads about 2.5k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 230 tokens; SKILL.md has 1,159 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~230
When it runs · the whole SKILL.md, loaded when a task matches
~2.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~11k

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 Infrasity-Labs/dev-gtm-claude-skills at commit 02cfefb, republished under its MIT licence (© Infrasity-Labs). 1,159 words, ~2,474 tokens.

Download SKILL.mdSave it as .claude/skills/api-docs-quality-report/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
api-docs-quality-report
description
Audits any API documentation site by crawling every endpoint page and scoring each one across 5 checks: description quality, OpenAPI spec presence, body param descriptions, response codes, and response schema completeness. Produces a polished interactive HTML report with a summary scorecard, site-wide pattern analysis, ranked top issues, and per-endpoint findings with specific fix guidance. Trigger this skill whenever a user provides a documentation URL and asks to audit, review, analyse, or check their API docs. Also trigger for: "do the same audit for X", "audit docs.company.com", "check the API docs at X", "run the API docs audit on X", "review the docs for Y API", or pastes a URL alongside words like audit, review, crawl, check, analyse, quality, completeness, or gaps. Always use this skill — do not attempt the audit without following this structured crawl-score-report workflow.
user-invokable
true
argument-hint
<docs_url>
license
MIT
metadata.version
1.0.0
metadata.category
api-docs

API Docs Audit Skill

Crawls every API reference endpoint page on a documentation site, scores each against 5 quality checks, detects site-wide patterns, and outputs an interactive HTML report matching the style of previously-generated audits in this session.


STEP 0 — COLLECT INPUT

You need exactly one input: the docs URL.

If the user hasn't provided it, ask:

Which API docs URL should I audit?

If the URL is provided, strip trailing slashes and confirm it before proceeding.

Special case — "do the same for X": If the user says "do the same" or "same audit for X", they want the identical workflow and HTML report format applied to the new URL. Proceed directly to Step 1.


STEP 1 — DISCOVER ALL ENDPOINT PAGES

1a. Try llms.txt first

Fetch <docs_url>/llms.txt.

If found:

  • Extract every line matching the pattern - [Page Title](URL): description
  • Filter to API reference pages only — look for paths containing any of: api-reference, api-reference/, /api/, /endpoints/, /rest/, /docs/, /reference/ or versioned paths (e.g., /v1/)
  • Exclude: overview/index pages (no HTTP method implied), SDK docs, CLI docs, Terraform docs, guides, quickstart pages
  • Store as ENDPOINT_PAGES[] — list of {title, url, description}

If not found or returns 404:

  • Fetch the docs homepage
  • Look for a nav sidebar or sitemap link referencing API/endpoints
  • Extract all API reference page URLs from the nav structure
  • Note in the report that llms.txt was unavailable
1b. Identify categories

Group discovered pages by their URL path prefix or nav section:

  • e.g. /api-reference/agents/ → Agents category
  • e.g. /api-reference/executions/ → Executions category
  • Pages at the root level of api-reference → Uncategorized or infer from title

Store CATEGORIES[] — list of {name, page_count, pages[]}.

Report discovery summary:

Found N endpoint pages across K categories. Fetching now...


STEP 2 — CHECK OPENAPI SPEC AVAILABILITY

Before fetching individual pages, check if a standalone OpenAPI spec exists.

Try these discovery methods in order (stop at first success):

  1. Inspect the Link HTTP header (RFC 8288) on the homepage or docs root for rel="openapi" or rel="describedby" — this is the standard discovery mechanism for API specifications
  2. <docs_url>/openapi.json
  3. <docs_url>/openapi.yaml
  4. <docs_url>/api/openapi.json
  5. Any URL referenced in llms.txt under "## OpenAPI Specs"

Result:

  • If accessible: SPEC_AVAILABLE = true, store the URL
  • If 404 on all attempts and no Link header found: SPEC_AVAILABLE = false

A missing spec is itself a top-priority finding — record it as Issue #1.


STEP 3 — FETCH AND PARSE ALL ENDPOINT PAGES

Fetch each URL in ENDPOINT_PAGES[]. For each page, extract:

3a. Page-level prose description

The text that appears above the OpenAPI block (or between the # title and the first ## OpenAPI heading). This is the human-written description.

3b. OpenAPI block

Look for a fenced code block with language hint yaml or json that contains an OpenAPI spec. Extract:

  • HTTP_METHOD — e.g. GET, POST, PUT, DELETE, PATCH
  • HTTP_PATH — e.g. /api/v1/agents/{agent_id}/execute
  • REQUEST_BODY_SCHEMA — the requestBody schema section (if any)
  • PARAMETERS — path + query params (if any)
  • RESPONSES — the full responses object
  • RESPONSE_200_SCHEMA — the schema under responses.200 or 201

If no OpenAPI block found, mark SPEC_INLINE = false.


STEP 4 — SCORE EACH ENDPOINT (5 CHECKS)

For every endpoint, evaluate all 5 checks. Store results as {check_name: "pass"|"warn"|"fail", current_state: string, fix_guidance: string}.

Read references/scoring-rules.md for the exact scoring criteria per check.

Check 1 — Endpoint Description Check 2 — OpenAPI Spec Check 3 — Body Param Descriptions Check 4 — Response Codes Check 5 — Response Schema


STEP 5 — DETECT SITE-WIDE PATTERNS

After scoring all endpoints, look for patterns that repeat across many pages.

A pattern qualifies if it affects ≥ 60% of endpoints:

Pattern to detectHow to identify
Universal missing error codesAll endpoints missing 401, 429, 500 etc.
Universal empty response schemasschema: {} on most endpoints
Free-form body schemasadditionalProperties: true on most request bodies
Inline spec only / broken canonical specAll pages embed spec inline but canonical 404s
One-liner descriptions everywhereDescriptions under 10 words on most pages
422-only validation errorsOnly FastAPI's 422 documented, not business errors

For each detected pattern, write a single paragraph summarising:

  • What the pattern is
  • How many endpoints it affects
  • Root cause (e.g. FastAPI auto-generation, missing middleware docs)
  • Impact on developer experience

Store as SITE_WIDE_PATTERNS[].


Show full SKILL.md (493 more words)Show less

STEP 6 — COMPILE TOP ISSUES

Rank the 10 most impactful issues across all findings. Prioritise by:

  1. Issues affecting the most endpoints
  2. Issues on the highest-traffic / most important endpoints
  3. Security-sensitive gaps (auth endpoints, credential endpoints with empty schemas)
  4. Deprecated endpoints with no migration path
  5. Spec availability (404 canonical spec blocks all SDK tooling)

For each issue, write:

  • A concise <strong>title</strong>
  • 1-2 sentence description with specific endpoint names or counts
  • Badge: FAIL or WARN

Store as TOP_ISSUES[] (max 10).


STEP 7 — BUILD SCORECARD

For each category, calculate:

  • total — endpoint count
  • pass_count — endpoints with all 5 checks passing
  • warn_count — endpoints with at least one WARN and no FAIL
  • fail_count — endpoints with at least one FAIL

Calculate overall totals.

Store as SCORECARD[].


STEP 8 — GENERATE HTML REPORT

Read references/html-template.md for the complete HTML structure, CSS variables, JavaScript, and all section markup.

Substitute all {{VARIABLE}} placeholders with real audit data, ensuring all values are HTML-escaped to prevent XSS.

Key variable map:

VariableSource
{{DOCS_URL}}Input URL
{{AUDIT_DATE}}Today's date
{{TOTAL_ENDPOINTS}}Count of ENDPOINT_PAGES
{{TOTAL_PASS}}Sum of all pass_count across categories
{{TOTAL_WARN}}Sum of all warn_count
{{TOTAL_FAIL}}Sum of all fail_count
{{SPEC_COUNT}}1 if SPEC_AVAILABLE, else 0
{{SCORECARD_ROWS}}Generated <tr> rows from SCORECARD
{{PATTERN_BOX}}Pattern box HTML (if SITE_WIDE_PATTERNS found)
{{TOP_ISSUES_HTML}}Generated issue row HTML from TOP_ISSUES
{{SIDEBAR_LINKS}}Generated sidebar <div class="sbl"> links
{{SECTIONS_HTML}}All section HTML for each category

For section HTML generation rules, see references/html-template.md → Section: SECTIONS_HTML.

Output the file to:

/mnt/user-data/outputs/<slug>-api-audit-report.html

Where <slug> is the domain name with dots replaced by hyphens (e.g. docs.kubiya.ai → kubiya-ai).

Then call present_files to deliver it.


ERROR HANDLING

SituationAction
llms.txt returns 404Crawl nav links from homepage; note in report
Individual endpoint page returns 404Skip it; add to "inaccessible pages" count in footer
Page has no OpenAPI blockScore Spec check as FAIL; still score other checks from prose
Page has no prose descriptionScore Description as FAIL with note "No prose description"
Endpoint page is robots.txt blockedNote in report; do not fetch
More than 200 endpoints foundBatch fetching — process in groups of 20, progress-report to user
Canonical spec accessibleNote as positive finding; do not flag as issue

WHAT NOT TO DO

  • ❌ Never start generating HTML before all pages are fetched and scored
  • ❌ Never skip an endpoint page — fetch every one listed in llms.txt
  • ❌ Never infer scores from page titles alone — fetch the actual page content
  • ❌ Never mark Response Codes as PASS just because 200 is documented
  • ❌ Never mark Response Schema as PASS for schema: {} — that is FAIL
  • ❌ Never mark Body Params as PASS for additionalProperties: true — that is WARN at minimum
  • ❌ Never report a pattern as site-wide unless it affects ≥ 60% of endpoints
  • ❌ Never put generic fix text — every fix_guidance must reference the specific endpoint

REFERENCE FILES

  • references/scoring-rules.md — Exact PASS/WARN/FAIL criteria for all 5 checks, with worked examples. Read before scoring any endpoint.

  • references/html-template.md — Complete HTML/CSS/JS template with all section markup, variable map, and rendering instructions. Read before writing any HTML.

© Infrasity-Labs, 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 3 other files (references) in skills/api-docs-quality-report of Infrasity-Labs/dev-gtm-claude-skills.

  • SKILL.md
  • README.md
  • references/html-template.md
  • references/scoring-rules.md

Open the folder on GitHubat commit 02cfefb

Compare with similar skills

API Docs Quality Report 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.

API Docs Quality Report compared with similar skills
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API Docs Quality Report this skillInfrasity-Labs/dev-gtm-claude-skills139—~2.5kAutomated safety check: PassMIT
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API Documentation Generatorluongnv89/claude-howto42k—~429Automated safety check: PassMIT
Dashclaw Shipucsandman/DashClaw310—~7.2kAutomated safety check: PassMIT
Agentic Workflows API Documentation Lungoagntcy/coffeeAgntcy112—~2.6kAutomated safety check: PassApache-2.0
Code DocumenterJeffallan/claude-skills12k—~1.5kAutomated safety check: PassMIT

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Works with

Categories

Questions about API Docs Quality Report

What does API Docs Quality Report do?

Audits any API documentation site by crawling every endpoint page and scoring each one across 5 checks: description quality, OpenAPI spec presence, body param descriptions, response codes, and…. API Docs Quality Report is an agent skill from Infrasity-Labs/dev-gtm-claude-skills. Audits any API documentation site by crawling every endpoint page and scoring each one across 5 checks: description quality, OpenAPI spec presence, body param descriptions, response codes, and response schema completeness.

When should I use API Docs Quality Report?

API Docs Quality Report fits situations like: this skill whenever a user provides a documentation URL and asks to audit; check their API docs; : do the same audit for X; audit docs.company.com.

How do I install API Docs Quality Report in Claude Code?

Run `npx skills add Infrasity-Labs/dev-gtm-claude-skills --skill api-docs-quality-report -a claude-code`. Or copy the skill folder (skills/api-docs-quality-report in Infrasity-Labs/dev-gtm-claude-skills) into .claude/skills/api-docs-quality-report in your project. Claude Code loads it when a task matches its description.

How do I install API Docs Quality Report in Codex?

Run `npx skills add Infrasity-Labs/dev-gtm-claude-skills --skill api-docs-quality-report -a codex`. Or copy the skill folder (skills/api-docs-quality-report in Infrasity-Labs/dev-gtm-claude-skills) into .agents/skills/api-docs-quality-report in your project. Codex loads it when a task matches its description.

Can I use API Docs Quality Report 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 Infrasity-Labs/dev-gtm-claude-skills --skill api-docs-quality-report -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/api-docs-quality-report, .gemini/skills/api-docs-quality-report, .github/skills/api-docs-quality-report and .opencode/skills/api-docs-quality-report in your project.

What does API Docs Quality Report need to run?

SKILL.md names no scripts, command-line tools or credentials: API Docs Quality Report is instructions for the agent only.

Does API Docs Quality Report 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 API Docs Quality Report 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 API Docs Quality Report use?

API Docs Quality Report is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does API Docs Quality Report use?

About 2.5k tokens (SKILL.md is roughly 9.9k 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 8.7k tokens, read only when the agent opens those files.

What are the alternatives to API Docs Quality Report?

Skills that share tags, products or a category with API Docs Quality Report: Nacos API Doc Update (nacos-group/nacos-group.github.io, 115 stars), API Documentation Generator (luongnv89/claude-howto, 42k stars), Dashclaw Ship (ucsandman/DashClaw, 310 stars) and Agentic Workflows API Documentation Lungo (agntcy/coffeeAgntcy, 112 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains API Docs Quality Report?

Infrasity-Labs (a GitHub user) maintains it in Infrasity-Labs/dev-gtm-claude-skills, which has 139 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on June 28, 2026.

Source: Infrasity-Labs/dev-gtm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.