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 YuDefine/nuxt-supabase-starter --skill clarifygit clone --depth 1 https://github.com/YuDefine/nuxt-supabase-starterWrote 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/yudefine/nuxt-supabase-starter/clarify)<a href="https://agentmods.dev/skills/yudefine/nuxt-supabase-starter/clarify"><img src="https://agentmods.dev/badge/skills/yudefine/nuxt-supabase-starter/clarify/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/yudefine/nuxt-supabase-starter/clarify"><img src="https://agentmods.dev/badge/skills/yudefine/nuxt-supabase-starter/clarify.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 | $0.00127 | $0.00863 |
| Opus 5 | $0.00063 | $0.00432 |
| Sonnet 5 | $0.00025 | $0.00173 |
| Haiku 4.5 | $0.00013 | $0.00086 |
Grade A, and why
clarify 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 today.
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
Clarify
當需求仍有細節不足、定義模糊或多種合理解讀時，先補足決策所需的上下文，再用好懂且可比較的選項向使用者提問，讓使用者拍板，而不是由 AI 自行補完。
SOP
Phase 1 -- 收斂本輪訪談缺口
- READ 讀取使用者需求、呼叫者 skill 指示、當前上下文與既有產物，確認本次要澄清的主題、決策邊界、指定提問面向，以及是否需要詳記問答紀錄。
- THINK 先讀取
rules/盤點高影響需求缺口與提問排序判準.md，再依其要求盤點需求中的缺漏、矛盾、模糊與未拍板決策，優先收斂影響範圍最大的 1 至 3 題作為本輪提問，並確保整個 clarify session 累計不超過 5 題。
Phase 2 -- 產出本輪 clarify 問題
- WRITE 先讀取
rules/Context與選項題撰寫判準.md、templates/clarify-question-round.md與templates/clarify-question-round.example.md，再依骨架與範例直接在對話中輸出本輪問題：每題都要先提供足以協助使用者判斷的Context，再提出一句清楚的總結之提問，最後用 Markdown 表格列出單選或多選Options、標示一個推薦選項與推薦原因，並固定提供Others讓使用者補充；不得使用 Ask Tool。 - WRITE 明確請使用者依題號回答選項編號，必要時在
Others補充說明；未收到回答前停止，不自行假設答案。
Phase 3 -- 依回答決定續問、收斂或記錄
- READ 讀取使用者對本輪問題的回答，整理已拍板決策、仍未解決缺口與新浮現的限制，判斷是否已足以讓呼叫者 skill 繼續。
- WRITE 若呼叫者 skill 要求詳記問答紀錄，先讀取
templates/clarify-log.md與templates/clarify-log.example.md，再依骨架更新本次 clarify session 的問答紀錄。 - THINK 若仍有高影響缺口且累計題數尚未達 5 題，回到 Phase 1 準備下一輪提問；若資訊已足夠，則輸出已確認決策、使用者補充與剩餘風險，交還呼叫者 skill 繼續後續流程。
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- today Changed · +1 lines 86df1eb005c7
- yesterday First seen · 36 lines · 127 tokens per session scan A f966bd077caa
clarify is a skill published in the GitHub repository YuDefine/nuxt-supabase-starter (45 stars, last pushed today), licensed MIT. It adds 127 tokens to every session and 863 once invoked, about $0.0006 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 2026-09-10.
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