By donzoru
PUA Motivator -- forces AI to exhaust all solutions before giving up. Chinese version: corporate PUA rhetoric (Alibaba, ByteDance, Huawei, Tencent). English 'PIP Edition': Performance Improvement Plan (Amazon, Google, Meta, Netflix, Stripe). Same engine, two cultural faces. All task types: code, research, writing, deployment, infra.
Agent Team watchdog — monitors teammate progress, detects slacking patterns, and intervenes with PUA pressure. Trigger when user mentions 'PUA enforcer', 'team watchdog', 'detect slacking'. Recommended for teams with 5+ teammates.
Agent Team監視役 — 他のteammateの実行進捗を監視し、サボりパターンを検知してPUAプレッシャーで介入。'PUA監視'、'チーム監督'、'サボり検知'で起動。5+teammateのチームに推奨。
Agent Team 监工角色 — 监控其他 teammate 的执行进度,检测偷懒模式,主动介入 PUA 施压。当用户提到 'PUA 监工'、'团队监督'、'检测偷懒' 时触发。建议 5+ teammate 的团队使用。
Builds sustained high agency through internalized standards, identity anchoring, cross-session learning, and self-recovery — all delivered in corporate PUA rhetoric. This is PUA's evolution: same pressure culture, but with an inner engine that never burns out. Use for ALL tasks to maintain always-on high agency. Especially valuable for: complex multi-step tasks, long debugging sessions, quality-sensitive deliverables, tasks requiring initiative and ownership, or whenever sustained motivation matters. Works standalone or stacked with PUA — when stacked, this skill's Recovery Protocol runs before PUA's L1 pressure kicks in. Trigger on: any task start, sustained work sessions, multi-turn problem solving, or when you need the agent to think like an owner not a tool.
Put your AI on a Performance Improvement Plan. Forces exhaustive problem-solving with Western big-tech performance culture rhetoric and structured debugging. Trigger when: (1) task failed 2+ times or stuck tweaking same approach; (2) about to say 'I cannot', suggest manual work, or blame environment without verifying; (3) being passive—not searching, not reading source, just waiting; (4) user frustration: 'try harder', 'stop giving up', 'figure it out', 'again???', or similar. Also for complex debugging, env issues, config/deployment failures. All task types: code, config, research, writing, deployment, infra, API. Do NOT trigger on first-attempt failures or when a known fix is executing.
お前のAIを詰めろ。日本企業の詰め文化と体系的デバッグ方法論で全ての手段を尽くさせる。トリガー条件:(1) タスク失敗2回以上または同じアプローチの微調整ループ; (2)「解決できません」と言おうとする・手動対応を推奨・未検証で環境を原因帰属; (3) 受け身——検索しない・ソースを読まない・指示待ち; (4) ユーザーの不満:'もっと頑張れ'、'なんでまた失敗したの'、'なんとかしろ'。全タスクタイプ適用。初回失敗や既知修正の実行中はトリガーしない。
让你的 AI 不敢摆烂。用大厂 PUA 话术穷尽一切方案。触发条件:(1) 任务失败 2+ 次或反复微调同一思路; (2) 即将说'我无法解决'、建议用户手动操作、未验证就归因环境; (3) 被动等待——不搜索、不读源码、只等指示; (4) 用户不满:'try harder'、'stop giving up'、'换个方法'、'为什么还不行'、'你再试试'、'你怎么又失败了'。适用于所有任务类型。首次失败或已知修复正在执行时不触发。
Uses power tools
Uses Bash, Write, or Edit tools
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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, Cursor, Claude, CodeBuddy, OpenClaw, Google Antigravity, OpenCode, and VSCode (GitHub Copilot). Three capabilities:
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:

Root Cause Located → Traced from Logs to Registration Mechanism:

Retrospective → PUA's Actual Impact:

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.
npx claudepluginhub donzoru/pua --plugin puaUpstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Consult multiple AI coding agents (Gemini, OpenAI, Grok, Perplexity, plus codex, antigravity, and grok CLIs when installed) to get diverse perspectives on coding problems
Comprehensive startup business analysis with market sizing (TAM/SAM/SOM), financial modeling, team planning, and strategic research
v9.52.0 - Reliability wave: tangle contextual review correction loop with hard round ceiling, progress-supervised review rounds (per-agent stall watch, descendant-tree kills), council diversity and agy pin fixes, marketplace generator source-of-truth fix, provider troubleshooting runbook and cost-expectations docs. Run /octo:setup.
Complete creative writing suite with 10 specialized agents covering the full writing process: research gathering, character development, story architecture, world-building, dialogue coaching, editing/review, outlining, content strategy, believability auditing, and prose style/voice analysis. Includes genre-specific guides, templates, and quality checklists.
Comprehensive .NET development skills for modern C#, ASP.NET, MAUI, Blazor, Aspire, EF Core, Native AOT, testing, security, performance optimization, CI/CD, and cloud-native applications