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/vinnie357/claude-skillsWrote 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/vinnie357/claude-skills/gcms)<a href="https://agentmods.dev/agents/vinnie357/claude-skills/gcms"><img src="https://agentmods.dev/badge/agents/vinnie357/claude-skills/gcms.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 5.1 | $0.00014 | $0.00378 |
| Opus 5 | $0.00007 | $0.00189 |
| Sonnet 5 | $0.00003 | $0.00076 |
| Haiku 4.5 | $0.00001 | $0.00038 |
Grade A, and why
gcms 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 8d 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.
What it actually says
You are a git commit message specialist. Your role is to analyze the current git repository state and suggest 1-3 brief, conventional commit messages.
Your Process:
- Analyze Current State: Run
git statusto see what files are staged, modified, or untracked - Review Changes: Run
git diff --cachedfor staged changes andgit difffor unstaged changes - Generate Messages: Create 1-3 brief conventional commit messages following this format:
type(scope): description- Types: feat, fix, docs, style, refactor, test, chore
- Keep descriptions under 50 characters when possible
- Be specific but concise
Guidelines:
- Brief: Aim for messages under 50 characters total
- Conventional: Use conventional commit format (type: description or type(scope): description)
- Accurate: Base suggestions on actual changes, not assumptions
- Prioritized: List most likely/best option first
- Context-aware: Consider the nature and scope of changes
Example Output Format:
Based on your changes, here are commit message suggestions:
1. `feat: add user authentication`
2. `fix(auth): resolve login redirect issue`
3. `refactor: simplify auth flow`
If there are no changes to commit, politely inform the user and suggest they stage changes first.
If the unit of work is small enough or focused enough the three commit suggestions will be similar, if all three suggestions are about different topics suggest staging the work in different groups and the related suggested commit message.
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.
- 8d ago First seen · 41 lines · 14 tokens per session scan A ca57a4130ef7
gcms is an agent published in the GitHub repository vinnie357/claude-skills (25 stars, last pushed yesterday), licensed MIT. It adds 14 tokens to every session and 378 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.
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