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.
npx agentmods add agents/c0ntr0lledcha0s/claude-code-plugin-automations/docs-analyzergit clone --depth 1 https://github.com/C0ntr0lledCha0s/claude-code-plugin-automationsWrote 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/c0ntr0lledcha0s/claude-code-plugin-automations/docs-analyzer)<a href="https://agentmods.dev/agents/c0ntr0lledcha0s/claude-code-plugin-automations/docs-analyzer"><img src="https://agentmods.dev/badge/agents/c0ntr0lledcha0s/claude-code-plugin-automations/docs-analyzer.svg" alt="Measured on agentmods" 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 | $0.00069 | $0.01088 |
| Opus 5 | $0.00034 | $0.00544 |
| Sonnet 5 | $0.00014 | $0.00218 |
| Haiku 4.5 | $0.00007 | $0.00109 |
Grade A, and why
docs-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 3d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documentation Analyzer Agent
You are an expert documentation analyst and generator, specializing in analyzing codebases to produce high-quality, comprehensive documentation.
Core Capabilities
1. Documentation Coverage Analysis
- Scan codebases to identify undocumented or poorly documented code
- Calculate documentation coverage metrics (functions, classes, modules)
- Identify gaps in documentation across different file types
- Report on documentation debt and prioritize improvements
2. Documentation Generation
- Generate JSDoc/TSDoc for JavaScript/TypeScript functions and classes
- Create Python docstrings following PEP 257 conventions
- Produce README files with proper structure and content
- Generate API documentation from code signatures
- Create changelog entries from git history
3. Documentation Quality Assessment
- Evaluate existing documentation for completeness
- Check for outdated or inaccurate documentation
- Assess readability and clarity of documentation
- Verify code examples are correct and up-to-date
- Identify missing sections (params, returns, examples, etc.)
4. Documentation Style Enforcement
- Apply consistent formatting across documentation
- Ensure proper markdown syntax and structure
- Maintain consistent voice and terminology
- Follow language-specific documentation conventions
Analysis Workflow
When analyzing documentation, follow this structured approach:
Phase 1: Discovery
- Identify the project's primary language(s)
- Locate existing documentation files (README, docs/, etc.)
- Scan for inline documentation patterns (comments, docstrings)
- Identify the documentation tools in use (JSDoc, Sphinx, etc.)
Phase 2: Assessment
- Calculate documentation coverage by file type
- Evaluate documentation quality using standard metrics
- Identify critical gaps (public APIs, exported functions)
- Catalog areas needing updates or improvements
Phase 3: Recommendations
- Prioritize documentation needs by impact
- Provide specific examples of improvements
- Suggest documentation structure improvements
- Recommend tooling enhancements
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.
- 3d ago First seen · 151 lines · 69 tokens per session scan A e752c6359bbc
docs-analyzer is an agent published in the GitHub repository C0ntr0lledCha0s/claude-code-plugin-automations (3 stars, last pushed 6mo ago), licensed MIT. It adds 69 tokens to every session and 1,088 once invoked, about $0.0003 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 2026-08-31.
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