ai-audit-docs

ai-audit-docs is a skill for Claude Code, Codex from arcasilesgroup/ai-engineering. It costs 115 tokens per session (1,624 once invoked), scanned A, original, Apache-2.0.

A documentation auditing skill that compares README and other documentation with the files, commands, links, versions, and features actually present in a repository.

In plain words
What is it for?
Use it to review README files and documentation folders and produce a severity-ranked report with the affected file, line, and incorrect claim.
Why use it?
It finds instructions that point to missing files, describe features that do not exist, or have become outdated, without changing the documentation.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions AGENTS.md.

Good fit Use it to review README files and documentation folders and produce a severity-ranked report with the affected file, line, and incorrect claim.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/arcasilesgroup/ai-engineering/ai-audit-docs
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add arcasilesgroup/ai-engineering --skill ai-audit-docs
Clone the repo
git clone --depth 1 https://github.com/arcasilesgroup/ai-engineering

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ai-audit-docs

README.md
[![agentmods](https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-audit-docs/github.svg)](https://agentmods.dev/skills/arcasilesgroup/ai-engineering/ai-audit-docs)
Your own site
<a href="https://agentmods.dev/skills/arcasilesgroup/ai-engineering/ai-audit-docs"><img src="https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-audit-docs/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ai-audit-docs

Your own site · 80×15
<a href="https://agentmods.dev/skills/arcasilesgroup/ai-engineering/ai-audit-docs"><img src="https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-audit-docs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 115 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,624 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00115 $0.01624
Opus 5.5 $0.00046 $0.00650
Sonnet 5.5 $0.00023 $0.00325
Haiku 4.5 $0.00012 $0.00162

Measured 22d ago against content hash 2753344016c4, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-audit-docs scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 22d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

(`git`, `ls`, `cat`, `curl`, `jq`, etc.) -> **warning** finding.
skills/ai-audit-docs/SKILL.md · 130 lines

How it starts

The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Audit docs against repo reality

Lifecycle

Lane: light Writes: nothing — report-only, never modifies files Read by: humans (consumed as a findings table) Dies: on completion Next: ai-verify (to validate fixes if user acts on findings)

What it produces

A ranked markdown table of findings. Every finding names the doc file, the line, the severity, and the broken claim.

Severity Meaning
critical Doc points users at something that does not exist — they will hit a wall
warning Claim is outdated or inaccurate but the doc is still roughly usable
info Cosmetic: stale version number, unused anchor, minor nit

Steps

  1. Determine scope. If the user gave a path, audit that. Otherwise default to README.md, AGENTS.md, and any docs/ directory at the repo root. Glob for **/*.md under docs if the directory exists. Never audit vendored or generated files (node_modules/, dist/, *.generated.*).

  2. Read every target doc. Extract all of these per file:

    • File links: markdown links pointing at local paths (e.g. ./path, ../path, path/to/file). Skip anchors (#section) and bare URLs — those are checked in step 3.
    • External URLs: bare http:// / https:// links. Collect for batch HEAD-check.
    • Command references: inline code or code blocks containing shell commands (npm run X, yarn X, make X, cargo X, python -m X, npx X). Strip arguments; extract just the command name.
    • Version strings: v1.2.3, 1.2.3, >=1.2.3, pinned deps in prose.
    • Feature claims: sentences that assert existence — "supports X", "includes X", "has X", "provides X", "X is built-in", "X is enabled by default".
  3. Cross-check file links. For each local path extracted from a markdown link:

    • Resolve it relative to the doc file's directory.
    • find or read to confirm the target exists. If not -> critical finding.
  4. Cross-check command references. For each command name:

    • grep the repo for a script/package-bin definition (package.json scripts, Makefile targets, Cargo.toml bin, setup.py/pyproject.toml entry points, shell scripts in bin/ or scripts/).
    • If no definition exists AND the command is not a well-known system binary (git, ls, cat, curl, jq, etc.) -> warning finding.
    • If a script IS defined, check that the arguments the doc uses still match the script's actual flags — flag mismatches -> info.

Read the full file on GitHub · 130 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 22d ago First seen · 130 lines · 115 tokens per session scan A 2753344016c4

Subscribe to this mod's changes

ai-audit-docs is a skill published in the GitHub repository arcasilesgroup/ai-engineering (61 stars, last pushed 2d ago), licensed Apache-2.0. It adds 115 tokens to every session and 1,624 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-24.

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