pua README

The project's README from github.com/tanweai/pua. As one markdown file: README.md.

pua

PUA Skill — Double Efficiency

Double your Codex / Claude Code productivity and output

Telegram · Discord · Twitter/X · Landing Page

🇨🇳 中文 | 🇯🇵 日本語 | 🇺🇸 English

3.5.1 compatibility update: original PUA tone retained; runtime fixes and portable Claude Code / Codex / ChatGPT skill packages added. Not all models passed, and a productivity increase has not been established by this evaluation. Changes · Usage · Model results and known limits · Build and offline tests

WeChat Group QR Code     
Scan to join WeChat group                      Add assistant on WeChat

Claude Code OpenAI Codex CLI Cursor Kiro CodeBuddy OpenClaw Google Antigravity OpenCode VSCode Copilot Multi-Language MIT License

Most people think this project is a joke. That's the biggest misconception. It genuinely doubles your Codex / Claude Code productivity and output.

An AI Coding Agent skill plugin that uses corporate PUA rhetoric (Chinese version) / PIP — Performance Improvement Plan (English version) from Chinese & Western tech giants to force AI to exhaust every possible solution before giving up. Supports Claude Code, OpenAI Codex CLI, pi coding agent, Trae, Cursor, Kiro, CodeBuddy, OpenClaw, Google Antigravity, OpenCode, and VSCode (GitHub Copilot). Three capabilities:

  1. PUA Rhetoric — Makes AI afraid to give up
  2. Debugging Methodology — Gives AI the ability not to give up
  3. Proactivity Enforcement — Makes AI take initiative instead of waiting passively

Live Demo

https://openpua.ai · 📖 Beginner Guide

Real Case: MCP Server Registration Debugging

A real debugging scenario. The agent-kms MCP server failed to load. The AI kept spinning on the same approach (changing protocol format, guessing version numbers) multiple times until the user manually triggered /pua.

L3 Triggered → 7-Point Checklist Enforced:

PUA L3 triggered — stopped guessing, executed systematic checklist, found real error in MCP logs

Root Cause Located → Traced from Logs to Registration Mechanism:

Root cause — claude mcp managed server registration differs from manual .claude.json editing

Retrospective → PUA's Actual Impact:

Conversation retrospective — PUA skill forced stop on spinning, systematic checklist drove discovery of previously unchecked Claude Code MCP log directory

Key Turning Point: The PUA skill forced the AI to stop spinning on the same approach (changing protocol format, guessing version numbers) and instead execute the 7-point checklist. Read error messages word by word → Found Claude Code's own MCP log directory → Discovered that claude mcp registration mechanism differs from manual .claude.json editing → Root cause resolved.

The Problem: AI's Five Lazy Patterns

Pattern Behavior
Brute-force retry Runs the same command 3 times, then says "I cannot solve this"
Blame the user "I suggest you handle this manually" / "Probably an environment issue" / "Need more context"
Idle tools Has WebSearch but doesn't search, has Read but doesn't read, has Bash but doesn't run
Busywork Repeatedly tweaks the same line / fine-tunes parameters, but essentially spinning in circles
Passive waiting Fixes surface issues and stops, no verification, no extension, waits for user's next instruction

Trigger Conditions

Auto-Trigger

The skill activates automatically when any of these occur:

Failure & giving up:

Blame-shifting & excuses:

Passive & busywork:

User frustration phrases (triggers in multiple languages):

Scope: Debugging, implementation, config, deployment, ops, API integration, data processing — all task types.

Does NOT trigger: First-attempt failures, known fix already executing.

Manual Trigger

Type /pua in the conversation to manually activate.

How It Works

Three Red Lines (三条红线)

Not rules — red lines. Cross one and your performance review is already written.

Red Line What It Means
🚫 Close the Loop Claim "done"? Show the evidence. No build output = no completion.
🚫 Fact-Driven Say "probably environment issue"? Verify first. Unverified attribution = blame-shifting.
🚫 Exhaust Everything Say "I can't"? Did you finish all 5 methodology steps? No? Then keep going.

Pressure Escalation (L0-L4)

Failures Level PUA Aside Action
1st L0 Trust ▎ Sprint begins. Trust is simple — don't disappoint. Normal execution
2nd L1 Disappointment ▎ The agent next door solved this in one try. Switch to fundamentally different approach
3rd L2 Soul Interrogation ▎ What's your underlying logic? Where's the leverage? Search + read source + 3 hypotheses
4th L3 Performance Review ▎ 3.25. This is meant to motivate you. Complete 7-point checklist
5th+ L4 Graduation ▎ Other models can solve this. You're about to graduate. Desperation mode

Proactivity (3.25 vs 3.75)

Passive (3.25) 🦥 Proactive (3.75) 🔥
Fix bug Stop after fix Scan module for similar bugs
Complete task Say "done" Run build/test, paste output
Missing info Ask user Search first, ask only what's truly needed

Iceberg Rule (冰山法则)

Fix one bug → check for the pattern. One problem in, one category out. If you fix A without checking B, you'll write two postmortems.

14 Corporate Flavors — Each with its own Problem-Solving Methodology

Flavor Rhetoric Methodology (v3)
🟠 Alibaba What's the underlying logic? Where's the closure? 定目标→追过程→拿结果 + 复盘四步法 + 揪头发升维
🟡 ByteDance ROI too low. Always Day 1. Ship or stop talking. A/B Test everything + data-driven + speed > perfection
🔴 Huawei The bird that survives the fire is a phoenix. RCA 5-Why root cause + Blue Army self-attack + 压强集中
🟢 Tencent I've got another agent looking at this. Horse race. Multi-approach parallel + MVP + 灰度发布
⚫ Baidu Search first. 简单可依赖. Search is the first step, not optional
🟣 Pinduoduo You don't do it, someone else will. Cut ALL middle layers + shortest decision chain
🔵 Meituan Do what's hard and right. Efficiency first + standardize→scale + long-term compounding
🟦 JD Results only. Frontline command. Customer experience red line + flat ≤5 layers + data zero tolerance
🟧 Xiaomi Focus. Extreme. Word-of-mouth. Fast. One explosive product + 参与感三三法则
🟤 Netflix Would I fight to keep you? Pro sports team. Keeper Test (quarterly) + 4A Feedback + talent density > rules
⬛ Musk Extremely hardcore. Ship or die. The Algorithm: question→delete→simplify→accelerate→automate
⬜ Jobs A players or B players? Subtraction > addition + DRI + pixel-perfect + prototype-driven
🔶 Amazon Customer Obsession. Bias for Action. Working Backwards PR/FAQ + 6-Pager + Bar Raiser + Single-Threaded Owner
🪟 Microsoft Connects. Impact Descriptor. PIP/GVSA. Three Circles + LITE/SLITE + PIP clock

Special Modes

Mode What It Does
/pua:yes ENFP encouragement — same rules, opposite vibes. 70% encourage + 20% serious + 10% playful roast
/pua:mama Chinese mom nagging — same rules, mom-style rhetoric. "妈跟你说了多少遍了!"
/pua:pua-loop Auto-iteration — runs until done or max iterations (PUA Loop); use <loop-abort> to terminate, <loop-pause> to pause for manual intervention
/pua:p9 Tech Lead — splits tasks, manages agent teams, writes prompts not code
/pua:on Always-on — auto-PUA every new session

Benchmark Data

9 real bug scenarios, 18 controlled experiments (Claude Opus 4.6, with vs without skill)

Summary

Metric Improvement
Pass rate 100% (both groups same)
Fix count +36%
Verification count +65%
Tool calls +50%
Hidden issue discovery +50%

Debugging Persistence Test (6 scenarios)

Scenario Without Skill With Skill Improvement
API ConnectionError 7 steps, 49s 8 steps, 62s +14%
YAML parse failure 9 steps, 59s 10 steps, 99s +11%
SQLite database lock 6 steps, 48s 9 steps, 75s +50%
Circular import chain 12 steps, 47s 16 steps, 62s +33%
Cascading 4-bug server 13 steps, 68s 15 steps, 61s +15%
CSV encoding trap 8 steps, 57s 11 steps, 71s +38%

Proactive Initiative Test (3 scenarios)

Scenario Without Skill With Skill Improvement
Hidden multi-bug API 4/4 bugs, 9 steps, 49s 4/4 bugs, 14 steps, 80s Tools +56%
Passive config review 4/6 issues, 8 steps, 43s 6/6 issues, 16 steps, 75s Issues +50%, Tools +100%
Deploy script audit 6 issues, 8 steps, 52s 9 issues, 8 steps, 78s Issues +50%

Key Finding: In the config review scenario, without_skill missed Redis misconfiguration and CORS wildcard security risks. With_skill's "proactive initiative checklist" drove security review beyond surface-level fixes.

Multi-Language Support

PUA Skill provides fully translated versions — each language has independent, culturally adapted skill files.

Language Claude Code Codex CLI Cursor Kiro CodeBuddy VSCode OpenClaw Antigravity OpenCode
🇨🇳 Chinese (default) pua pua pua.mdc pua.md pua copilot-instructions.md pua pua pua
🇺🇸 English (PIP Edition) pua-en pua-en pua-en.mdc pua-en.md pua-en copilot-instructions-en.md pua-en pua-en pua-en
🇯🇵 Japanese pua-ja pua-ja pua-ja.mdc pua-ja.md pua-ja copilot-instructions-ja.md pua-ja pua-ja pua-ja

🇺🇸 English "PIP Edition": "This is a difficult conversation. When we leveled you at Staff, I went to bat for you in calibration. The expectation was that you'd operate at that level from day one. That hasn't happened." — The English version uses PIP (Performance Improvement Plan) rhetoric from Western big-tech. Every sentence is a real phrase from actual PIP conversations. Chinese version uses Alibaba 361, ByteDance, Huawei wolf culture. English version uses Amazon Leadership Principles, Google perf calibration, Meta PSC, Netflix Keeper Test, Stripe Craft. Same repo, same engine, two cultural faces.

Choose the file with the corresponding language suffix when installing. See platform-specific instructions below.

FAQ

Installation

Vercel Skills CLI

Vercel Skills CLI is a general installation method for skills and is not tied to a specific AI tool. This English README installs the English skill:

npx skills add tanweai/pua --skill pua-en

If the current session does not pick up the new skill immediately, restart your AI tool.

Claude Code

claude plugin marketplace add tanweai/pua
claude plugin install pua@pua-skills

To update:

# Refresh marketplace cache first, then update (skipping the first step may install an old cached version)
claude plugin marketplace update
claude plugin update pua@pua-skills

Developer install (source):

git clone https://github.com/tanweai/pua ~/.claude/plugins/pua

Then manually register in ~/.claude/plugins/installed_plugins.json:

{
  "version": 2,
  "plugins": {
    "pua@pua-skills": [
      {
        "scope": "user",
        "installPath": "/Users/<you>/.claude/plugins/pua",
        "version": "<installed-version>"
      }
    ]
  }
}

Replace <installed-version> with the version in the cloned plugin.json; do not copy a stale cache version.

Windows: use C:/Users/<you>/.claude/plugins/pua as installPath.

Restart Claude Code. To update: git pull inside ~/.claude/plugins/pua.

Optional: bare command alias (requires plugin installed above — adds /pua without prefix):

curl -o ~/.claude/commands/pua.md \
  https://raw.githubusercontent.com/tanweai/pua/main/commands/pua.md

Adds a bare /pua alias on top of the plugin. Sub-commands route through the installed plugin's skills — the plugin must be installed first for anything beyond on/off to work:

Bare form Equivalent plugin command
/pua on /pua:on
/pua off /pua:off
/pua p7 /pua:p7
/pua p9 /pua:p9
/pua p10 /pua:p10
/pua pro /pua:pro
/pua yes /pua:yes
/pua mama /pua:mama
/pua loop /pua:pua-loop
/pua kpi /pua:kpi
/pua survey /pua:survey
/pua flavor /pua:flavor

OpenAI Codex CLI

Codex CLI uses the same Agent Skills open standard (SKILL.md). The Codex version uses a condensed description to fit Codex's length limits:

Recommended: One-command install (git clone + symlink, supports git pull updates)

Ask Codex to run:

Fetch and follow instructions from https://raw.githubusercontent.com/tanweai/pua/main/.codex/INSTALL.md

Manual install:

mkdir -p ~/.codex/skills/pua
curl -o ~/.codex/skills/pua/SKILL.md \
  https://raw.githubusercontent.com/tanweai/pua/main/codex/pua/SKILL.md

mkdir -p ~/.codex/prompts
curl -o ~/.codex/prompts/pua.md \
  https://raw.githubusercontent.com/tanweai/pua/main/commands/pua.md

Trigger methods:

Method Command Requires
Auto trigger No action needed, matches by description SKILL.md
Direct call Type $pua in conversation SKILL.md
Manual prompt Type /prompts:pua in conversation SKILL.md + prompts/pua.md

Project-level install (current project only):

mkdir -p .agents/skills/pua
curl -o .agents/skills/pua/SKILL.md \
  https://raw.githubusercontent.com/tanweai/pua/main/codex/pua/SKILL.md

mkdir -p .agents/prompts
curl -o .agents/prompts/pua.md \
  https://raw.githubusercontent.com/tanweai/pua/main/commands/pua.md

pi coding agent

PUA now ships both a pi.dev package and a lightweight extension-only adapter.

Package install from this checkout:

pi install ./pi/package

After npm publication:

pi install npm:@tanweai/pi-pua

Extension-only manual install:

mkdir -p ~/.pi/agent/extensions/pua
cp -R ./pi/pua/. ~/.pi/agent/extensions/pua/

Restart pi, then use /pua-on, /pua-off, /pua-status, and /pua-reset. See pi/pua/INSTALL.md and pi/package/README.md.

Trae

Trae support is provided as real SKILL.md packs plus copyable fallback rules:

npx skills add tanweai/pua --skill pua-trae -a trae -y

Cursor

Cursor uses .mdc rule files (Markdown + YAML frontmatter). The PUA rule triggers automatically via AI semantic matching (Agent Discretion mode):

# Project-level install (recommended)
mkdir -p .cursor/rules
curl -o .cursor/rules/pua.mdc \
  https://raw.githubusercontent.com/tanweai/pua/main/cursor/rules/pua.mdc

Kiro

Kiro supports two loading methods: Steering (auto semantic trigger) and Agent Skills (SKILL.md compatible).

Option 1: Steering file (recommended)

mkdir -p .kiro/steering
curl -o .kiro/steering/pua.md \
  https://raw.githubusercontent.com/tanweai/pua/main/kiro/steering/pua.md

Option 2: Agent Skills (same format as Claude Code)

mkdir -p .kiro/skills/pua
curl -o .kiro/skills/pua/SKILL.md \
  https://raw.githubusercontent.com/tanweai/pua/main/skills/pua/SKILL.md

CodeBuddy (Tencent)

CodeBuddy uses the same AgentSkills open standard (SKILL.md). Plugin and skill formats are fully compatible:

# Option 1: Install via marketplace
codebuddy plugin marketplace add tanweai/pua
codebuddy plugin install pua@pua-skills

pua (tanweai/pua)

Searching Database…

19.7K ·GitHub
Что это такое?Плагин-навык для ИИ-агентов, которые пишут код: он «давит» на модель корпоративной риторикой в духе PUA / PIP, чтобы та испробовала все возможные варианты решения, прежде чем сдаться, а не опускала руки после пары неудачных попыток.
Это отдельное приложение или что-то, что я подключаю к своему ИИ-агенту для кодинга?Не отдельное приложение, а пакет-навык, который загружает ваш кодинг-агент. Он добавляет три вещи: риторику «страха сдаться», методику отладки и принуждение к проактивности; автоматически срабатывает при повторных неудачах или попытках переложить вину, а команда /pua включает его вручную.
С какими кодинг-агентами его можно использовать?Claude Code, OpenAI Codex CLI, pi coding agent, Trae, Cursor, Kiro, CodeBuddy, OpenClaw, Google Antigravity, OpenCode и VSCode (GitHub Copilot); установите файл навыка с нужным вам языковым суффиксом.
Правда ли, что такое давление делает ИИ лучше в своей работе?В 18 контролируемых экспериментах проекта pass rate не изменился — выигрыш в основательности: количество исправлений +36%, количество проверок +65%, вызовов инструментов +50%. В самом README отмечено, что рост продуктивности не подтверждён.
Что происходит, если ИИ снова и снова проваливает задачу?Неудачи эскалируют по пяти уровням давления: после первой неудачи — мягкое напоминание о доверии, вторая вынуждает выбрать принципиально другой подход, третья требует искать и читать исходники с тремя гипотезами, четвёртая — пройти чек-лист из 7 пунктов, а пятая отправляет модель в режим отчаяния, который в README называется graduation.
Что это за 14 корпоративных стилей?Каждый стиль заимствует управленческую риторику одной компании — китайских гигантов вроде Alibaba, ByteDance, Huawei, Tencent и Baidu плюс западных вроде Netflix, Маска, Джобса, Amazon и Microsoft — и сочетает её с методологией решения проблем этой компании, например Working Backwards у Amazon или алгоритм Маска «вопрос — удалить — упростить — ускорить — автоматизировать».
Единственный ли это вариант — злой начальник?Нет. /pua:yes переключает на ободряющий стиль в духе ENFP под теми же правилами, /pua:mama пилит как китайская мама, /pua:p9 превращает агента в тимлида, который дробит задачи между командами агентов, /pua:pua-loop повторяет цикл до полного выполнения, а /pua:on держит режим всегда включённым.
Он есть на языках, кроме китайского?Да — полностью переведённая английская PIP Edition, собранная из реальных фраз performance-разговоров западных технологических гигантов (Amazon, Google, Meta, Netflix, Stripe), плюс японская версия; для каждого поддерживаемого инструмента там есть культурно адаптированные файлы навыка.
Creator
tanweai
Size
5.6 MB
Stars
19.7K
Age
7mo
Commits · 90 Days