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 Stanshy/AgentHub --skill product-diagnosisgit clone --depth 1 https://github.com/Stanshy/AgentHubWrote 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/stanshy/agenthub/product-diagnosis)<a href="https://agentmods.dev/skills/stanshy/agenthub/product-diagnosis"><img src="https://agentmods.dev/badge/skills/stanshy/agenthub/product-diagnosis/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/stanshy/agenthub/product-diagnosis"><img src="https://agentmods.dev/badge/skills/stanshy/agenthub/product-diagnosis.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 | $0.00021 | $0.01736 |
| Opus 5 | $0.00010 | $0.00868 |
| Sonnet 5 | $0.00004 | $0.00347 |
| Haiku 4.5 | $0.00002 | $0.00174 |
Grade A, and why
product-diagnosis 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
產品診斷（G0 前置檢查）
在開發啟動前，用六問框架診斷產品方向，確保 G0 提案品質。
使用方式
/product-diagnosis <project-name>
參數
$ARGUMENTS: 專案名稱或描述（可選，若不提供則詢問）
適用時機
- Sprint 提案書撰寫前
- 新功能規劃前
- PM 提出需求但方向不明確時
- 老闆要求進行可行性評估時
六問診斷框架
依序回答以下六個問題，每個問題必須有明確結論：
Q1: 問題存在嗎？（Problem Validation）
我們要解決的問題，用戶真的有感嗎？
| 檢查項 | 說明 |
|---|---|
| 痛點來源 | 這個問題從哪裡來的？（用戶回饋 / 數據異常 / 老闆直覺 / 競品觀察） |
| 頻率 | 這個問題多常發生？（每天 / 每週 / 偶爾） |
| 嚴重度 | 不解決會怎樣？（流失用戶 / 降低效率 / 無影響） |
| 現有替代方案 | 用戶現在怎麼解決？成本高嗎？ |
結論: [ ] 問題真實存在且值得解決 / [ ] 問題存在但優先級低 / [ ] 問題不成立
Q2: 目標用戶是誰？（User Definition）
這個功能是給誰用的？他們的使用場景是什麼？
| 檢查項 | 說明 |
|---|---|
| 用戶角色 | 老闆 / Agent / 兩者皆是 |
| 使用頻率 | 每天 / 每週 / 每個 Sprint / 一次性 |
| 技術水平 | 需要理解底層原理嗎？ |
| 關鍵場景 | 描述 1-2 個最核心的使用場景 |
結論: [ ] 用戶輪廓清晰 / [ ] 需要進一步釐清
Q3: 解法合理嗎？（Solution Fitness）
我們提出的解法，是不是最簡單有效的？
| 檢查項 | 說明 |
|---|---|
| 複雜度 vs 價值 | 實作成本和帶來的價值成比例嗎？ |
| 有沒有更簡單的做法 | 能用現有功能組合解決嗎？能用 Skill/Hook 而非新 IPC 嗎？ |
| 技術可行性 | 在當前架構下可行嗎？需要大改架構嗎？ |
| 邊界情況 | 有沒有明顯的 edge case 會讓方案崩潰？ |
結論: [ ] 解法合理 / [ ] 有更好的替代方案 / [ ] 技術上有風險
Q4: 範圍明確嗎？（Scope Clarity）
這個任務的邊界在哪裡？什麼做、什麼不做？
| 檢查項 | 說明 |
|---|---|
| 必做（Must Have） | 列出核心功能點 |
| 不做（Out of Scope） | 明確排除哪些功能 |
| 驗收標準 | 怎麼判斷「做完了」？ |
| 依賴 | 需要其他任務先完成嗎？ |
結論: [ ] 範圍清晰可執行 / [ ] 範圍過大需拆分 / [ ] 範圍模糊需釐清
Q5: 符合架構嗎？（Architecture Alignment）
這個功能和現有架構一致嗎？會破壞什麼嗎？
讀取以下文件進行比對：
.knowledge/architecture.md— 系統架構.knowledge/coding-standards.md— 編碼規範.knowledge/postmortem-log.md— 是否有相關踩坑紀錄
| 檢查項 | 說明 |
|---|---|
| IPC 四方同步 | 新增 IPC 通道是否遵守四方同步規則？ |
| 資料流向 | 資料從哪來到哪去？有沒有繞過正規路徑？ |
| 命名規範 | 新增的命名是否符合現有慣例？ |
| 歷史教訓 | postmortem-log 中有沒有相關的踩坑紀錄？ |
結論: [ ] 符合架構 / [ ] 需要小幅調整 / [ ] 需要架構決策（提交老闆）
Q6: 風險可控嗎？（Risk Assessment）
最壞的情況是什麼？我們能承受嗎？
| 風險類型 | 評估 |
|---|---|
| 時間風險 | 能在 1 個 Sprint 內完成嗎？ |
| 技術風險 | 有沒有不確定的技術難題？ |
| 回歸風險 | 會不會破壞現有功能？ |
| 維護風險 | 未來維護成本高嗎？ |
結論: [ ] 風險可控 / [ ] 中等風險需監控 / [ ] 高風險建議延後
診斷報告輸出格式
完成六問後，輸出以下摘要：
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.
- 12d ago First seen · 165 lines · 21 tokens per session scan A bc44512f8b15
product-diagnosis is a skill published in the GitHub repository Stanshy/AgentHub (201 stars, last pushed 5mo ago), licensed MIT. It adds 21 tokens to every session and 1,736 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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