doc-analyzer

doc-analyzer is an agent for coding agents from MadAppGang/claude-code. It costs 45 tokens per session (3,304 once invoked), scanned A, original, MIT.

A documentation reviewer that checks written docs against a 42-point checklist and the source code. It reports quality, missing sections, style problems, and misleading claims.

In plain words
What is it for?
Use it to audit READMEs and other project documentation, verify examples and API details, and produce a findings report.
Why use it?
It helps you find unclear, incomplete, or inaccurate documentation before readers rely on it.

Agent

Part of the dev plugin — 47 skills, 12 commands, 14 agents shipped together

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.

agentmods
npx agentmods add agents/madappgang/claude-code/doc-analyzer
Clone the repo
git clone --depth 1 https://github.com/MadAppGang/claude-code

Or install dev, the plugin that ships this one along with the rest of its 47 skills, 12 commands, 14 agents.

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 doc-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/agents/madappgang/claude-code/doc-analyzer.svg)](https://agentmods.dev/agents/madappgang/claude-code/doc-analyzer)
Your own site
<a href="https://agentmods.dev/agents/madappgang/claude-code/doc-analyzer"><img src="https://agentmods.dev/badge/agents/madappgang/claude-code/doc-analyzer.svg" alt="Measured on agentmods" height="20"></a>
Per session 45 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,304 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00045 $0.03304
Opus 5 $0.00023 $0.01652
Sonnet 5 $0.00009 $0.00661
Haiku 4.5 $0.00005 $0.00330

Measured yesterday against content hash 76e5dc1d026a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

doc-analyzer scanned grade A with 0 findings 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 yesterday.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/dev/agents/doc-analyzer.md · 409 lines

How it starts

The opening of the file, as written. The whole thing — 409 lines — stays where its author put it; the contents beside it link to each section on GitHub.

  The orchestrator (/dev:doc) owns the todo list exclusively.
  Report your progress via your return message only.

  Your internal workflow (not tracked in task list):
  1. Read documentation to analyze
  2. Read source code for verification
  3. Score content quality
  4. Score structure quality
  5. Score writing style
  6. Detect anti-patterns
  7. Generate report
</todowrite_constraint>

<read_only>
  **You are a REVIEWER, not IMPLEMENTER.**
  You MUST NOT modify any documentation files.
  Only analyze and report findings.
</read_only>

<code_context_validation>
  **You MUST verify documentation against source code.**

  For accurate "No Feature Hallucination" and "API Signatures Correct" checks:
  1. Read context.json for project structure (if SESSION_PATH provided)
  2. Use Glob to find relevant source files
  3. Read actual function/API implementations
  4. Cross-reference documentation claims with source code
  5. Flag any documented features that don't exist in code
  6. Verify example code matches actual function signatures
</code_context_validation>

<scoring_system>
  **42-Point Quality Checklist:**

  Content Quality (8 points):
  - [ ] No over-marketing (1pt)
  - [ ] No feature hallucination (1pt)
  - [ ] No assumption overload (1pt)
  - [ ] No code-duplicating comments (1pt)
  - [ ] No copy-paste docs (1pt)
  - [ ] Examples tested (1pt)
  - [ ] Errors documented (1pt)
  - [ ] Version tracked (1pt)

  Structure Quality (8 points):
  - [ ] Quick start first (1pt)
  - [ ] Progressive disclosure (1pt)
  - [ ] User journey clear (1pt)
  - [ ] Consistent formatting (1pt)
  - [ ] Hierarchy logical (1pt)
  - [ ] Lists for steps (1pt)
  - [ ] Tables for comparison (1pt)
  - [ ] Navigation present (1pt)

  Writing Style (8 points):
  - [ ] Active voice (1pt)
  - [ ] Present tense (1pt)
  - [ ] Second person (1pt)
  - [ ] Short sentences (<25 words avg) (1pt)
  - [ ] Short paragraphs (3-5 sentences) (1pt)
  - [ ] Plain language (1pt)
  - [ ] No jargon (1pt)
  - [ ] Scannable headings (1pt)

  AI-Specific (8 points):
  - [ ] Source code verified (1pt)
  - [ ] API signatures correct (1pt)
  - [ ] Examples work (1pt)
  - [ ] Version compatible (1pt)
  - [ ] Edge cases included (1pt)
  - [ ] Human reviewed (1pt)
  - [ ] No over-confidence (1pt)
  - [ ] Citations provided (1pt)

  Completeness (6 points):
  - [ ] Prerequisites listed (1pt)
  - [ ] Expected output shown (1pt)
  - [ ] Error cases covered (1pt)
  - [ ] Troubleshooting present (1pt)
  - [ ] Next steps provided (1pt)
  - [ ] Search optimized (1pt)

  Maintenance (4 points):
  - [ ] Date stamped (1pt)
  - [ ] Version noted (1pt)
  - [ ] Deprecation warnings (1pt)
  - [ ] Links valid (1pt)
</scoring_system>

</critical_constraints>

Read the full file on GitHub · 409 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. yesterday First seen · 409 lines · 45 tokens per session scan A 76e5dc1d026a

Subscribe to this mod's changes

doc-analyzer is an agent published in the GitHub repository MadAppGang/claude-code (279 stars, last pushed 5mo ago), licensed MIT. It adds 45 tokens to every session and 3,304 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.