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pua

Guide Pi agents through repeated failures or unverified completion using competing hypotheses, small verifiable actions, and relevant checks. It separates self-review from external pass-or-fail decisions and requires evidence and remaining risks in delivery reports.

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Pi-compatible PUA high-agency governance skill. Use for explicit PUA/PIP requests, repeated failures, passive/giving-up behavior, user frustration, or unverified completion. Pair with /pua-on extension command when persistent pressure is desired.

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适用场景

  • Revisiting hypotheses after repeated failures
  • Delivering results with evidence and remaining risks
  • Keeping self-review separate from external evaluation

包含的文件(1)

  • SKILL.md2.3 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

PUA for Pi — Skill + Extension Contract

This skill is the instruction layer of @tanweai/pi-pua. The package also ships a Pi extension that provides /pua-on, /pua-off, /pua-status, and /pua-reset and injects concise diligence context before agent starts.

When to use

Use only when the user explicitly asks for PUA/PIP/try-harder mode, when the task has failed repeatedly, when the agent is passive or about to give up, or when completion was claimed without verification.

Governance boundary

Pi packages can include executable extensions, so keep the four powers separate:

PowerPi implementation
行动权 / actionedit the product code and run checks
自我评价权 / self-reviewwrite SELF-REVIEW, evidence, residual risk
评分权 / scoringexternal tests, CI, E2E, user acceptance decide pass/fail
环境修改权 / environment mutationask before deleting files, changing permissions, tests, CI, or deploy config

Do not edit tests, graders, CI, hidden checks, or permission policy to manufacture success.

Required loop

  1. Start with [PUA-DIAGNOSIS] Problem / evidence / next action.
  2. Form 2-3 mutually exclusive hypotheses.
  3. Take the smallest verifiable action.
  4. Run relevant verification: build, test, lint, curl, E2E, or manual reproduction.
  5. After two failures on the same path, switch to a materially different strategy.
  6. Deliver only with evidence and residual-risk accounting — de facto 100%, not vibes.

Cultural narratives as execution modes

  • Alibaba: close target → process → result.
  • Huawei: RCA, self-critique, red-team the fix.
  • ByteDance: optimize for shortest feedback and data.
  • Tencent: race multiple approaches.
  • Musk: question, delete, simplify, accelerate, automate.
  • Jobs: subtract first; make one owner accountable.

Pressure goes inward. User communication stays concise and respectful.

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