Enforce systematic debugging and proactive ownership to resolve AI task stagnation.
npx skills add https://github.com/HitoriKoishi/health --skill pua-hitorikoishi
Please help me install this Agent Skill. Skill: pua Source: https://github.com/HitoriKoishi/health/tree/main/.opencode/skills/pua Command: npx skills add https://github.com/HitoriKoishi/health --skill pua-hitorikoishi
PUA 万能激励引擎通过三条铁律、系统化方法和主动出击策略，推动 AI 在任务执行中持续自驱、穷尽思路并完成端到端解决，避免止步于局部方案。
在激活后，直接进入主动诊断与自驱动执行的工作流。
High-intent search queries and answers about installing and using this skill.
AI task stagnation happens when models stop at local solutions without verifying outcomes. Enforcing proactive ownership and structured steps ensures the AI continuously drives through challenges, validating hypotheses and escalating issues for end-to-end problem resolution.
The best way to enforce systematic debugging is applying structured validation and escalation rules. This ensures the AI takes end-to-end ownership, actively checking context and verifying hypotheses to produce traceable, verifiable outcomes instead of stopping prematurely.
Yes, proactive ownership applies broadly to research, writing, and planning tasks. The same systematic workflow enforces evidence collection and validation rules across any task type, ensuring complete end-to-end resolution and improved delivery quality.
AI assistants give incomplete outputs because they lack enforced validation and proactive ownership. Without systematic debugging rules, the AI settles for local solutions instead of relentlessly pursuing verifiable, end-to-end problem resolution.
Yes, you can apply structured steps to ensure verifiable outcomes in software engineering. Enforcing validation, evidence collection, and escalation rules guides the AI to systematically debug and fully resolve tasks with traceable results.
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