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HanHan666666
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pua

Exhaust viable solutions and verify outcomes before reporting completion.

10|4|Updated Mar 18, 2026
Search Tags:#automation#debugging#ownership#evidence#failure-modes#proactivity#pua
One-click install
npx skills add https://github.com/HanHan666666/flutter-linglong-store --skill pua-hanhan666666
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pua
Source: https://github.com/HanHan666666/flutter-linglong-store/tree/main/.agents/skills/pua
Command: npx skills add https://github.com/HanHan666666/flutter-linglong-store --skill pua-hanhan666666

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a proactive, owner-driven engine that exhausts all viable solutions, prevents premature surrender, and ensures end-to-end delivery by verifying outcomes before reporting completion.

Core Features & Use Cases

  • Proactive problem solving: Exhausts all viable approaches, checks context, and accelerates fixes across coding, debugging, research, writing, and planning tasks.
  • End-to-end ownership: Enforces validation, regression checks, and closure with downstream impact assessment.
  • Failure-mode guided responses: Uses structured patterns to escalate, switch strategies, and avoid placeholders like “please check again” without action.
  • Use Case: In a debugging session, when typical fixes fail, it systematically tests alternatives, verifies changes, and reports a verified resolution with evidence.

Quick Start

请从所有可行方案中穷尽并自行验证后，给出一个端到端的解决方案。

Frequently Asked Questions about pua

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prevent AI from stopping at incomplete fixes during debugging?▼

End-to-end ownership means the AI must exhaust all viable solutions, perform regression checks, assess downstream impact, and validate results with evidence before reporting a task as complete.

What is failure-mode guided problem solving for automation tasks?▼

Failure-mode guided problem solving uses structured patterns to escalate issues, switch strategies, and avoid placeholders like “please check again”, ensuring the AI systematically tests alternatives and verifies changes.

Can I use this approach for research and planning tasks beyond coding?▼

Yes, this approach applies across coding, debugging, research, writing, planning, and operational tasks, triggering when failures rebound or guidance stalls to ensure proactive problem resolution.

How do I verify AI-generated solutions before closing a task?▼

Verify AI-generated solutions by enforcing evidence-backed validation, running regression checks, and assessing downstream impact to ensure the fix is complete and rebound failures do not occur.

Why does my AI assistant give up prematurely when typical fixes fail?▼

AI assistants give up prematurely when they lack a proactive ownership engine to exhaust alternatives; enforcing a structured failure-mode response prevents this surrender and drives end-to-end closure.

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