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 skills add terrylica/cc-skills --skill quenchgit clone --depth 1 https://github.com/terrylica/cc-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/skills/terrylica/cc-skills/quench)<a href="https://agentmods.dev/skills/terrylica/cc-skills/quench"><img src="https://agentmods.dev/badge/skills/terrylica/cc-skills/quench/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/skills/terrylica/cc-skills/quench"><img src="https://agentmods.dev/badge/skills/terrylica/cc-skills/quench.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00033 | $0.00269 |
| Opus 5 | $0.00016 | $0.00134 |
| Sonnet 5 | $0.00007 | $0.00054 |
| Haiku 4.5 | $0.00003 | $0.00027 |
Grade A, and why
quench 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 4d 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
/floating-clock:quench
Terminate any running FloatingClock process.
Self-Evolving Skill: This skill improves through use. If the process pattern stops matching (binary path change) — fix this file immediately, don't defer. Only update for real, reproducible issues.
Steps
if pgrep -f "FloatingClock.app/Contents/MacOS/floating-clock" >/dev/null 2>&1; then
pkill -f "FloatingClock.app/Contents/MacOS/floating-clock"
echo "FloatingClock quit."
else
echo "FloatingClock is not running."
fi
Post-Execution Reflection
After this skill completes, check before closing:
- Did
pkillactually terminate the process? — If it lingered, escalate tokill -9and update the script. - Did the process pattern still match? — If the binary path moved, refresh the
pgrep/pkillregex.
Only update if the issue is real and reproducible — not speculative.
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.
- 4d ago First seen · 32 lines · 33 tokens per session scan A 4081ffcb4549
quench is a skill published in the GitHub repository terrylica/cc-skills (66 stars, last pushed today), licensed MIT. It adds 33 tokens to every session and 269 once invoked, about $0.0002 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 2026-09-05.
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