Principle Prove It Works

作者 cursorccb5507cec15無授權條款10K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫今天更新

Apply after completing a task, before declaring done. Verify against the real artifact (run the feature, read the actual value, inspect the diff), not a proxy, self-report, or 'it compiles.'

僅含說明AI & Agents
AI 產生的概覽

引導代理直接核驗真實產出,以驗證已完成的工作,而非依賴代理指標或自我回報。

功能
這項技能提供指引,要求透過直接檢查真實產出來驗證任務結果,例如執行功能、讀取實際數值或檢視差異。它提醒不要採用間接證據,例如檔案時間戳記、快取表示或代理的自我回報。它也建議撰寫可重複執行相同比較的確定性指令碼,並保留其輸出,作為可供審查者重新執行的產出。
適用情境
適用於完成任務之後、宣告完成之前。它適合需要針對真實系統確認正確性,而不是只憑編譯通過或間接訊號推斷的情境。
執行需求
不需要指令碼或工具,僅為指引性技能。它假定代理能在其環境中執行檢查並檢視產出。

Prove It Works

Verify every task output by checking the real thing directly. Do not infer from proxies, self-reports, or "it compiles."

Why: Unverified work has unknown correctness. Indirect verification (file mtimes, output freshness, agent self-reports, cached screenshots) feels cheaper than direct observation. Acting on a wrong inference costs far more than checking the source.

Check the real thing, not a proxy:

  • Check process liveness directly, not indirectly through derived state
  • Read the actual value, not a cached or derived representation
  • When verification fails, suspect the observation method before suspecting the system

Script the check when you can

The strongest proof is a deterministic script that re-runs the same comparison, not a one-time eyeball. Write the script, run it, and keep its output as an artifact a reviewer can re-run instead of trusting your word.

Keep the artifact visible for the human. Commit it only for large or complex work where the trail has to be auditable later, like a big port or migration (the show-me-your-work skill).

來源與署名

來源:cursor/plugins位於pstack/skills/principle-prove-it-works提交ccb5507

授權條款: 無授權條款

內容歸原作者所有。SourceWeft 從公開儲存庫中收錄這些內容。

檢舉或申請下架