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/joneqian/claude-skills-suiteWrote 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/joneqian/claude-skills-suite/update-docs)<a href="https://agentmods.dev/commands/joneqian/claude-skills-suite/update-docs"><img src="https://agentmods.dev/badge/commands/joneqian/claude-skills-suite/update-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.
<a href="https://agentmods.dev/commands/joneqian/claude-skills-suite/update-docs"><img src="https://agentmods.dev/badge/commands/joneqian/claude-skills-suite/update-docs.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 | $0.00000 | $0.00163 |
| Opus 5 | $0.00000 | $0.00081 |
| Sonnet 5 | $0.00000 | $0.00033 |
| Haiku 4.5 | $0.00000 | $0.00016 |
Grade C, and why
update-docs scanned grade C 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 9d 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.
Harvests environment variableshighData exfiltration
Enumerating or grepping the environment for keys collects credentials unrelated to what the mod says it does.
- Extract all environment variables This is a copy
91% identical to update-docs — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Update Documentation
Sync documentation from source-of-truth:
-
Read package.json scripts section
- Generate scripts reference table
- Include descriptions from comments
-
Read .env.example
- Extract all environment variables
- Document purpose and format
-
Generate docs/CONTRIB.md with:
- Development workflow
- Available scripts
- Environment setup
- Testing procedures
-
Generate docs/RUNBOOK.md with:
- Deployment procedures
- Monitoring and alerts
- Common issues and fixes
- Rollback procedures
-
Identify obsolete documentation:
- Find docs not modified in 90+ days
- List for manual review
-
Show diff summary
Single source of truth: package.json and .env.example
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.
- 9d ago First seen · 32 lines · 0 tokens per session scan C 752fc73c254d
update-docs is a command published in the GitHub repository joneqian/claude-skills-suite (32 stars, last pushed 7mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 163 tokens. A static security scan graded it C with 1 finding (harvests environment variables). It is 91% identical to update-docs, differing in 5 lines, and is treated as a copy.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.