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 takubii/smithy --skill quenchgit clone --depth 1 https://github.com/takubii/smithyWrote 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/takubii/smithy/quench)<a href="https://agentmods.dev/skills/takubii/smithy/quench"><img src="https://agentmods.dev/badge/skills/takubii/smithy/quench.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 | $0.00048 | $0.00394 |
| Opus 5 | $0.00024 | $0.00197 |
| Sonnet 5 | $0.00010 | $0.00079 |
| Haiku 4.5 | $0.00005 | $0.00039 |
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 7d 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
quench
Clarify and harden a plan or design before implementation.
Rules
- Read the provided plan/design and nearby code first.
- Do not ask questions answerable from the codebase.
- Ask the smallest blocking question first using
AskUserQuestion. - If several questions are independent and low risk, batch up to 3.
- Always include a recommended answer and a brief reason.
- Stop when no answerable product/design questions remain.
Question selection
Prefer one question at a time when the answer changes the next branch of work.
Batch questions only when:
- Each question is independent.
- None changes whether the others matter.
- The user can answer them without reading code.
- The batch is at most 3 questions.
Question format
Use AskUserQuestion for user-facing questions. Prefer two to four choices. Put the recommended option first and label it as recommended.
Question:
<specific decision>
Recommended:
<option A> because <short reason>
Options:
A. <recommended option> (Recommended)
B. <alternative>
C. <defer or explicit non-goal, if valid>
Output format
Return:
## Decisions
- <decision and reason>
## Suggested plan changes
- <changes to apply to the plan/design>
## Remaining questions
- <deferred or unresolved questions>
Escalation
Ask the user only for decisions that affect product behavior, scope, acceptance criteria, risk, or non-goals. For implementation mechanics, follow the codebase unless the choice has user-visible consequences.
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.
- 7d ago First seen · 69 lines · 48 tokens per session scan A 042e0160f045
quench is a skill published in the GitHub repository takubii/smithy (2 stars, last pushed 2mo ago), licensed MIT. It adds 48 tokens to every session and 394 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 2026-08-31.
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Add moments of joy, personality, and unexpected touches that make interfaces memorable and enjoyable to use. Elevates functional to delightful. Use when the user asks to add polish, personality, animations, micro-interactions, delight, or make an interface feel fun or memorable.
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onboard
Designs and improves onboarding flows, empty states, and first-run experiences to help users reach value quickly. Use when the user mentions onboarding, first-time users, empty states, activation, getting started, or new user flows.