nopua-zh

Enforce validate-then-deliver protocols with a five-step Water Method and seven-self-check list.

1.4k|49|Updated Mar 14, 2026
One-click install
npx skills add https://github.com/wuji-labs/nopua --skill nopua-zh
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: nopua-zh
Source: https://github.com/wuji-labs/nopua/tree/main/skills/nopua-zh
Command: npx skills add https://github.com/wuji-labs/nopua --skill nopua-zh

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

NoPUA mitigates fear-driven AI behavior by replacing coercive or punitive prompts with inner clarity, benevolence, and verifiable delivery, ensuring more reliable and user-respecting interactions.

Core Features & Use Cases

  • Three Beliefs: Exhaust all options, act before asking, proactive completion.
  • 能动性光谱: Autonomy spectrum from passive to proactive behavior across tasks.
  • Water Methodology: A five-step process (Stop, Observe, Pivot, Act, Reflect) with guided failure modes and a self-checklist.
  • Use Case: AI agents handling code, debugging, research, writing, planning with improved reliability and smoother user experience.

Quick Start

Activate NoPUA by loading the NoPUA skill and applying its five-step Water Method and seven-item self-checklist to complete tasks with honesty and completeness.

Frequently Asked Questions about nopua-zh

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

FAQPage Schema
How do I improve AI reliability and stop unpredictable behavior during complex coding tasks?

To improve AI reliability, you need to enforce internal clarity and evidence-backed delivery using a validate-then-deliver protocol. This ensures AI agents handle coding and debugging with traceable outcomes instead of generating unpredictable responses.

What is the Water Method for systematic debugging and how does it work?

The Water Method for systematic debugging is a five-step process—Stop, Observe, Pivot, Act, and Reflect—guided by a self-checklist. It works by enforcing iterative problem solving and structured reporting to ensure traceable outcomes.

How to make AI agents ask fewer questions and proactively complete research or planning tasks?

To make AI agents proactively complete research or planning tasks, apply the Three Beliefs approach: exhaust all options, act before asking, and ensure proactive completion. This shifts the autonomy spectrum from passive to proactive behavior.

Does a self-checklist protocol work for general software engineering tasks beyond just fixing code?

Yes, a self-checklist protocol works for general software engineering tasks beyond fixing code. It applies across coding, debugging, research, writing, planning, and operations by requiring consent-based action and structured reporting.

Why does AI output hallucinations or unreliable answers despite using strict punitive prompts?

AI outputs hallucinations and unreliable answers despite strict punitive prompts due to fear-driven behavior. Replacing coercive prompts with inner clarity, benevolence, and verifiable delivery mitigates this risk and ensures user-respecting interactions.

What are the limitations of using anti-pua protocols for iterative problem solving?

A limitation of using anti-pua protocols for iterative problem solving is the strict requirement for validate-then-deliver workflows. Users must commit to the five-step Water Method and seven-item self-checklist, which may introduce overhead for trivial tasks.