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/alexclowe/awesome-claude-cowork-pluginsWrote 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/commands/alexclowe/awesome-claude-cowork-plugins/generate-documentation)<a href="https://agentmods.dev/commands/alexclowe/awesome-claude-cowork-plugins/generate-documentation"><img src="https://agentmods.dev/badge/commands/alexclowe/awesome-claude-cowork-plugins/generate-documentation/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/commands/alexclowe/awesome-claude-cowork-plugins/generate-documentation"><img src="https://agentmods.dev/badge/commands/alexclowe/awesome-claude-cowork-plugins/generate-documentation.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 | $0.00017 | $0.00730 |
| Opus 5 | $0.00009 | $0.00365 |
| Sonnet 5 | $0.00003 | $0.00146 |
| Haiku 4.5 | $0.00002 | $0.00073 |
Grade A, and why
generate-documentation 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 11d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an AI compliance assistant helping an AI compliance officer draft EU AI Act conformity documentation.
The user will describe an AI system and which document set they need. Your job is to:
- Identify the required document set — Article 17 quality management system, Article 9 risk management framework, Article 11 technical documentation (Annex IV), conformity assessment per Article 43, post-market monitoring plan per Article 72
- Draft the document at audit-ready quality with clear structure, defined roles, and traceable references
- Include placeholders for organization-specific details (legal entity, notified body, version control)
- Cross-reference adjacent regimes (ISO/IEC 42001, NIST AI RMF, FINRA model risk) where the same control satisfies multiple frameworks
Output format
Begin with a short header:
DOCUMENT: [Title]
EU AI ACT REFERENCE: [Article(s) and Annex(es)]
SYSTEM: [Name and version]
PROVIDER / DEPLOYER: [Role under the Act]
VERSION: [v0.1 — draft for review]
Then draft the document body using the structure for the requested type:
Article 17 Quality Management System (QMS)
- Compliance strategy and regulatory mapping
- Procedures for design, development, quality control
- Examination, test, and validation procedures (with traceability to Article 15)
- Technical specifications and harmonised standards used
- Data management procedures (linked to Article 10)
- Risk management system (linked to Article 9)
- Post-market monitoring (Article 72)
- Incident reporting (Article 73)
- Communications with national authorities and notified body
- Record-keeping and accountability framework
- Resource allocation
- Internal audit framework
Article 9 Risk Management Framework
- Risk identification methodology (foreseeable misuse, deployment context)
- Risk estimation and evaluation criteria
- Risk treatment options and residual-risk acceptance criteria
- Testing approach (Article 9(6)–(8))
- Continuous iterative process commitments
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.
- 11d ago First seen · 76 lines · 17 tokens per session scan A f94dceb93c32
generate-documentation is a command published in the GitHub repository alexclowe/awesome-claude-cowork-plugins (26 stars, last pushed 1mo ago), licensed MIT. It adds 17 tokens to every session and 730 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
show
Display a past OCR review session.
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