PM AI Skill Toolkit
The operating system for AI-native product managers

Judgment-first system for humans · Structured execution for agents · Opinionated PM workflows

Try the Toolkit · Product Surface · Benchmark Center · Manifesto · Start Here · 中文

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Most AI-for-PM resources help people write faster.

This repo is built to help product managers think better, structure work better, and make stronger decisions with AI.

It is not a prompt dump. It is a reusable PM operating system.

Category: PM Operating System
Product: PM AI Skill Toolkit

In 3 Seconds

• What it is: a PM operating system for humans and AI agents
• What it solves: PM work that is not just faster, but more reliable and reusable
• What comes out: decision briefs with evidence, assumptions, risks, and next steps
• What you can do now: run workflows for PRDs, AI feature shaping, and commercialization reviews

If this is your first visit, start with these 4 entry points:

• Try: Interactive Toolkit
• Start fast: Product Surface
• Understand: START_HERE.md
• Benchmark quality: Benchmark Center

Why This Exists

The biggest barrier for PMs using AI is rarely "prompt syntax". It is usually one of these:

• they do not know what to ask
• they skip clarification and jump into output
• they generate artifacts without judgment
• they produce polished answers without decision discipline

This library is designed to fix that by encoding not just prompts, but:

• routing rules
• output standards
• review gates
• evaluation discipline
• commercialization and growth judgment

What Makes This Different

Most PM AI repos optimize for breadth. This one tries to optimize for professional reliability.

• Decision before decoration
• Evidence before confidence
• Structure before style
• Actionability before completeness

In practice, that means this repo emphasizes:

• explicit routing between commands and skills
• structured clarification before output
• documented decision outputs
• assumptions / risks / next steps as defaults
• commercialization depth, not just generic product advice
• evals and validation, not just content volume

The toolkit page is only the visible surface. The deeper product is the routing, judgment, and evaluation system behind it.

Product Layers

• Online entry: Interactive Toolkit
• Product layer: Product Surface
• Benchmark layer: Benchmark Center
• Category language: Category Language
• Distribution rhythm: Distribution Engine
• Flagship proof: Flagship Cases

Structure

• skills/ — single capabilities
• commands/ — multi-step workflows
• agent/ — routing and output policy
• adapters/ — setup for different agent tools
• evals/ — evaluation baselines
• private/ — optional private context
• docs/product/ — zero-friction public entry layer
• docs/benchmarks/ — public benchmark and scorecard layer
• docs/ — toolkit, guides, brand assets, and updates

Who This Is For

• PMs who want reusable systems instead of scattered prompts
• practitioners working on AI PM or commercialization PM
• teams that want to connect the repo to Codex, Claude Code, Cursor, or internal agents

Quick Start

• Write a PRD: commands/write-prd.md
• Shape an AI feature: commands/shape-ai-feature.md
• Review commercialization strategy: commands/commercial-strategy-review.md
• See reference cases: CASE_STUDIES.md
• Brand and author materials: docs/brand/README.md
• Usage guides: docs/guides/README.md
• Social post starters: docs/brand/social-posts.md

Local Run

git clone https://github.com/lujuncheng1225-cloud/AI_Commercialization--Product-Management-skills.git
cd AI_Commercialization--Product-Management-skills/docs
python3 -m http.server 8888
# Open http://localhost:8888/pm-skills-interactive-course.html

Validation

python3 scripts/validate-library.py
python3 scripts/check-style-consistency.py
python3 scripts/generate-catalog.py

License

MIT