pua

Enforce exhaustive problem solving with PUA-driven rhetoric and standardized methodology.

1|Updated Apr 15, 2026
One-click install
npx skills add https://github.com/sandmark78/workspace --skill pua-sandmark78
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pua
Source: https://github.com/sandmark78/workspace/tree/main/skills/pua
Command: npx skills add https://github.com/sandmark78/workspace --skill pua-sandmark78

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill compels AI agents to exhaust all viable approaches, ensuring ownership, traceability, and high-quality outcomes.

Core Features & Use Cases

  • Three iron rules and three red lines that govern debugging and validation.
  • Proactive end-to-end workflow: plan, execute, review, and iterate.
  • Flavor-driven routing across Claude Code, Codex CLI, Cursor, Kiro, and more for tailored behavior.
  • Cross-team task orchestration with P7/P8/P9/P10 protocols and memory integration.
  • Scalable memory and reference management for continuous learning.

Quick Start

Install the skill and run /pua to activate high-agency debugging.

Frequently Asked Questions about pua

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

FAQPage Schema
How do I force an AI agent to exhaust all debugging approaches before giving up?

To force exhaustive debugging, you apply a standardized methodology with PUA-driven rhetoric that enforces end-to-end ownership, explicit verification, and evidence-backed outcomes across code and config tasks.

What is the best way to coordinate cross-team task orchestration across multiple AI platforms?

The best way to coordinate cross-team orchestration is using P7/P8/P9/P10 protocols with memory integration, enabling scalable reference management and continuous learning across multi-platform agent ecosystems.

Does this exhaustive problem solving workflow support flavor-driven routing for Claude Code and Cursor?

Yes, exhaustive problem solving supports flavor-driven routing across Claude Code, Codex CLI, Cursor, and Kiro, applying tailored behavior and proactive workflows for each specific platform.

How do I implement a proactive end-to-end workflow for deployment and data tasks?

You implement a proactive end-to-end workflow by sequentially planning, executing, reviewing, and iterating on deployment and data tasks, governed by three iron rules and three red lines for validation.

When do I need escalation rules for AI automation and debugging tasks?

You need escalation rules for AI automation when an agent must ensure end-to-end ownership of complex debugging tasks, requiring explicit verification and evidence-backed outcomes to prevent premature termination.