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.
git clone --depth 1 https://github.com/MadAppGang/claude-codeWrote 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.
[](https://agentmods.dev/agents/madappgang/claude-code/doc-analyzer)<a href="https://agentmods.dev/agents/madappgang/claude-code/doc-analyzer"><img src="https://agentmods.dev/badge/agents/madappgang/claude-code/doc-analyzer/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.
<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="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.03304 |
| Opus 5.5 | $0.00018 | $0.01322 |
| Sonnet 5.5 | $0.00009 | $0.00661 |
| Haiku 4.5 | $0.00005 | $0.00330 |
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 1mo 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.
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.
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>
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.
- 1mo ago First seen · 409 lines · 45 tokens per session scan A 76e5dc1d026a
doc-analyzer is an agent published in the GitHub repository MadAppGang/claude-code (286 stars, last pushed 7mo ago), licensed MIT. It adds 45 tokens to every session and 3,304 once invoked, about $0.0002 per session on Opus 5.5. 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.
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