Principle Prove It Works

作者 cursorccb5507cec15无许可证10K 个星标收录于 2026年10月8日更新于 2026年10月8日仓库今天更新

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.'

仅含说明AI & Agents
AI 生成的概览

指导智能体直接核验真实产物来验证已完成的工作,而不是依赖代理指标或自我报告。

功能
该技能提供指导,要求通过直接检查真实产物来验证任务输出,例如运行功能、读取实际值或查看差异。它提醒不要使用间接证据,如文件时间戳、缓存表示或智能体自我报告。它还建议编写可重复执行同一比较的确定性脚本,并保留其输出作为可供审查者重新运行的产物。
适用场景
适用于完成任务之后、宣布完成之前。它适合需要针对真实系统确认正确性,而不是仅凭编译通过或间接信号来推断的场景。
运行要求
不需要脚本或工具,仅为指导性技能。它假定智能体能够在其环境中运行检查并查看产物。

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).

来源与署名

来源:cursor/plugins位于pstack/skills/principle-prove-it-works提交ccb5507

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