Enforce autonomous end-to-end problem solving with evidence-backed verification.
npx skills add https://github.com/sandmark78/workspace --skill pua-ja
Please help me install this Agent Skill. Skill: pua-ja Source: https://github.com/sandmark78/workspace/tree/main/skills/pua-ja Command: npx skills add https://github.com/sandmark78/workspace --skill pua-ja
This skill enforces autonomous, end-to-end problem solving and relentless proactivity to avoid stagnation, especially when facing ambiguous tasks or repeated failures.
Begin an end-to-end proactive problem solving session on your current task.
High-intent search queries and answers about installing and using this skill.
To stop AI hesitation, you need a structured proactivity framework that enforces autonomous investigation, tool execution, and evidence-backed verification to drive tasks to completion.
Autonomous debugging is a structured diagnostic workflow where AI surfaces root causes, tests hypotheses, executes commands, and documents results to break through stagnation and repeated failures.
Enforce evidence-backed verification by requiring your AI to search sources, read files, execute commands, and provide traceable evidence within an escalation path before finalizing planning or research outcomes.
Yes, a proactive AI workflow applies directly to ambiguous code deployment and writing tasks by championing ownership, pushing progress forward autonomously, and verifying results without waiting for user prompts.
The best way to structure relentless proactivity is implementing a framework with defined proactivity levels, ensuring the AI drives experimentation and verification end-to-end while documenting results for future reuse.
AI stagnates on ambiguous tasks due to lack of structured ownership; fixing it requires enforcing an autonomous problem-solving workflow that mandates tool usage, hypothesis testing, and traceable evidence generation.
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