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GitHub stars License: CC BY-NC-SA 4.0 PRs Welcome Version Claude Code Plugin Skills
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
来源文件:README.md
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║ 70 battle-tested skills + 6 command workflows ║
║ Claude Code • Cursor • Codex • n8n • OpenClaw • and more ... ║
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║ v0.83 • July 17, 2026 • CC BY-NC-SA 4.0 ║
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70 battle-tested PM frameworks, ready for Claude, Codex, ChatGPT, and any agent that can read structured knowledge.
Generic AI output is a PM's worst enemy. When you tell your agent "write a PRD" without shared context, you get a generic document that no stakeholder trusts and no engineer can act on.
This library gives both you and your AI agent the same professional foundation: the why behind each framework, the failure modes to avoid, and the judgment to apply them correctly. You stop repeating yourself. Your agent stops guessing. The work gets better.
The goal is dual — functional and pedagogic in equal measure. Skills equip agents to do PM work at a professional level, and they teach the human PM the reasoning behind each framework — so you can explain it, adapt it, and pass it on. Neither is a byproduct of the other.
Navigate by what you're actually trying to accomplish:
Framing and strategy
Stakeholder alignment
Customer discovery and research
Prioritization and roadmapping
Writing PM deliverables
Validation and experimentation
Finance and growth
Market and competitive intelligence
Career and leadership transitions
AI product work
Choose your setup:
| I use... | Get this | Notes |
|---|---|---|
| Claude Desktop or Claude Web | pm-skills-starter-pack.zip | Unzip, then upload the individual skill ZIPs to Claude Skills |
| Claude Code | Plugin marketplace | claude /plugin marketplace add deanpeters/Product-Manager-Skills |
| Codex | pm-skills-codex.zip | Installs .agents/skills and AGENTS.md |
| Not sure | pm-skills-starter-pack.zip | Start here |
All downloads: GitHub Releases
Each pack below is a ZIP of upload-ready skill ZIPs — unzip, then upload individuals to Claude Skills:
| Pack | Download | What's inside |
|---|---|---|
| Starter | pm-skills-starter-pack.zip | Core skills across all categories |
| Discovery | 02-discovery-pack.zip | Research, interviewing, synthesis |
| Strategy | 03-strategy-pack.zip | Positioning, roadmapping, prioritization |
| Delivery | 04-delivery-pack.zip | PRDs, stories, epics |
| AI PM | 05-ai-pm-pack.zip | Context engineering, orchestration, readiness |
| Market Intel | 06-market-intel-pack.zip | The full Market Intelligence Suite: disciplines, investigation chain, frameworks, monitors |
| All skills | 99-all-skills-pack.zip | All 70 skills |
Not ready to wire skills into your agent setup? Run the local playground first and kick the tires in your browser.
pip install -r app/requirements.txt
streamlit run app/main.py
What you can do:
Multi-provider support: Anthropic, OpenAI, Ollama. API keys via environment variables only (no in-app key entry).
Docs: app/STREAMLIT_INTERFACE.md · app/.env.example
Feedback welcome via GitHub Issues or LinkedIn.
Skills are organized in three tiers that build on each other:
┌────────────────────────────────────────────────────────┐
│ WORKFLOW SKILLS (19) │
│ Complete end-to-end PM processes (days to weeks) │
│ Example: run a full discovery cycle or write a PRD │
└────────────────────────────────────────────────────────┘
↓ orchestrates
┌────────────────────────────────────────────────────────┐
│ INTERACTIVE SKILLS (27) │
│ Guided discovery — 3-5 questions, then recommendations│
│ Example: "Which prioritization framework fits here?" │
└────────────────────────────────────────────────────────┘
↓ uses
┌────────────────────────────────────────────────────────┐
│ COMPONENT SKILLS (24) │
│ Templates for specific PM deliverables (30-90 min) │
│ Example: write a user story with acceptance criteria │
└────────────────────────────────────────────────────────┘
Interactive skills use an Adaptive Decision Ladder. Instead of dumping a framework at you, an interactive skill asks 3-5 targeted questions about your specific context, then offers numbered recommendations — each with a clear "use this when" rationale. You pick a path. The skill executes it and explains the why as it goes. If you want to just learn the framework without doing the work, you can ask that too — the skill coaches you either way. This is ABC — Always Be Coaching — in practice.
Full catalog: catalog/INDEX.md — all 70 skills with descriptions, or browse skills/ directly.
Every SKILL.md follows the same structure:
| Section | What it contains |
|---|---|
| Frontmatter | name, description, type, intent, best_for, scenarios |
| Purpose | What this skill does and when to reach for it |
| Input | What you can bring (with example invocations) — inline input is used, not re-asked, and arriving empty-handed is fine: the skill walks you through it |
| Key Concepts | Frameworks, definitions, anti-patterns — with vocabulary explained |
| Application | Step-by-step instructions an agent (or human) can follow |
| Examples | Real-world cases showing both good and bad versions |
| Common Pitfalls | Named failure modes with consequences and corrections |
| References | Related skills and external frameworks |
The best_for frontmatter field lists 3-5 specific scenarios where the skill is most useful — helpful for quickly scanning whether a skill fits your situation.
Why no $ARGUMENTS templating? Other skill libraries use Claude Code's $ARGUMENTS substitution for input. We deliberately don't: it only expands in Claude Code (it renders as literal syntax in Claude Desktop/Web, Codex, and the Streamlit playground), and it teaches the human reader nothing. Instead, every skill has a plain-language ## Input section that works on every runtime — and makes clear you can show up with full context, partial context, or nothing at all and be guided through the rest. Full rationale in CONTRIBUTING.md.
Claude Code · Claude Desktop · Claude Web · OpenAI Codex · ChatGPT · Cursor · Windsurf · n8n · LangFlow · CrewAI · Gemini · any agent that reads structured markdown
See docs/Platform Guides for PMs.md for platform-specific setup.
| Document | Purpose |
|---|---|
| Using PM Skills 101 | Beginner-friendly orientation — setup without technical overload |
| Platform Guides for PMs | Tool-by-tool setup chooser for every supported platform |
| Using PM Skills with Claude | Claude Code + GitHub ZIP upload for Claude Desktop/Web |
| Using PM Skills with Codex | Local workspace + GitHub-connected Codex on ChatGPT |
| Using PM Skills with ChatGPT | GitHub app, Custom GPT Knowledge, and Project-based usage |
| Using PM Skills with Slash Commands 101 | Turn skills into reusable slash commands like /pm-story |
| Add-a-Skill Utility Guide | End-to-end guide for generating and validating new skills |
| Market Intelligence Suite Summary | The 14-skill competitive/market research suite: disciplines, chain, and which skill to run when |
| Building PM Skills | How raw PM content gets distilled into agent-ready skills |
| START_HERE.md | 60-second onboarding for local repo users |
v0.83 — July 17, 2026 · The Market Intelligence Suite
autonomous-investigation — the protocol for research that proceeds without you. Question budgets, a search-plan gate, Fact / Inference / Assumption labels on every claim, do-not-invent lists, and stable diffable schemas, so investigations can run on a schedule and you can diff this quarter against lasttam-sam-som-calculator (three entry modes, including autonomous bottom-up research) and company-intel (Executive Signal Refresh rerun pattern — Then/Now diffs and Dropped Language: what leaders stop saying is often the strongest signal)v0.82 — July 8, 2026
incoming-request-advisor (Interactive) — drop in a Slack ping, email, mandate, or escalation and get a structured breakdown that separates the literal ask from the real job-to-be-done, reads sender power and stake, and points you toward a reply. Ships with a copy/paste template so you can run it by hand too/dist — no terminal, no Releases tab. Read the plain-language README, scan the CATALOG, and download any skill or pack straight from the repo. Built for PMs who just want the skillsv0.81 — July 4, 2026
## Input section: what to bring, what happens to context you supply up front (it's used, not re-asked), and reassurance that arriving empty-handed is fine — the guided flow covers the restargument-hint autocomplete for Claude Code users; deliberately no $ARGUMENTS templating — it breaks on every other runtime and teaches the reader nothing (why)$ARGUMENTS in the bodyagent-orchestration-advisor (Interactive) — the multi-agent workflow design skill was referenced everywhere but only existed on an orphaned commit; recovered from git history and brought up to current standardsv0.80 — June 19, 2026
stakeholder-identification (Component) — comprehensive stakeholder brainstorm using allies/audiences/influencers, R/P/D marking, equity lens, and bias check; narrows to priority targetsstakeholder-mapping (Component) — two complementary grids (Power × Interest + Impact × Power); comparing outputs reveals who you're under-engaging relative to how much the product affects themstakeholder-engagement-advisor (Interactive) — per-stakeholder engagement planning via Adaptive Decision Ladder: three questions on profile, power/impact, and context deliver tailored message framing, medium, cadence, and a named next actionAll three adapted from the MITRE Innovation Toolkit via the companion repo MITRE ITK Skills — worth a bookmark if you work in discovery, facilitation, or cross-functional product strategy.
v0.79 — May 15, 2026
organic-growth-advisor — McKinsey Growth Pyramid triage for new segments, geographies, channels, or productspm-skill-creator — interactive skill for designing repo-compliant skills via guided conversation.claude-plugin/plugin.json that silently blocked Claude Code skill discoveryPM_MAX_INPUT) and path traversal protection to helper scriptsFound a gap? Have a PM framework worth formalizing? The bar is pedagogic — skills must teach the why, not just the how.
See CONTRIBUTING.md for guidelines, or open an issue to start a conversation.
CC BY-NC-SA 4.0 — non-commercial use with share-alike.
Everything in this repository — every skill, template, and doc — is licensed CC BY-NC-SA 4.0. There is no mix of licenses here.
Some skills note in their Provenance sections that they were adapted from product-manager-prompts, Dean's earlier prompt library. That repo has the same author, so there is no license conflict: a license grants permissions to other people, and a copyright holder is free to adapt and relicense their own work. Those Provenance lines are lineage — a breadcrumb back to where an idea started — not a license dependency. No third-party MIT-licensed text is incorporated anywhere in this library.
In plain terms:
The companion prompt library, product-manager-prompts, carries the same CC BY-NC-SA 4.0 license as of its v2.3.0, with its own plain-language permissions (stricter on commercial use) — see its LICENSING.md, which governs that repo.
name: discovery-process
argument-hint: "[problem hypothesis]"
description: Run a full discovery cycle from problem hypothesis to validated solution. Use when a team needs a structured path through framing, interviews, synthesis, and experiments.
intent: >-
Guide product managers through a complete discovery cycle—from initial problem hypothesis to validated solution—by orchestrating problem framing, customer interviews, synthesis, and experimentation skills into a structured process. Use this to systematically explore problem spaces, validate assumptions, and build confidence before committing to full development—avoiding "build it and they will come" syndrome and ensuring you're solving real customer problems.
type: workflow
theme: discovery-research
best_for:
- "Running a full discovery cycle from hypothesis to validated solution"
- "Investigating a retention or churn problem systematically"
- "Setting up continuous discovery as an ongoing practice"
scenarios:
- "I have a hypothesis that B2B customers struggle with onboarding and want to validate it before building anything"
- "Our activation rate dropped 15% this quarter and I need to run discovery to find out why"
estimated_time: "30-60 min"Guide product managers through a complete discovery cycle—from initial problem hypothesis to validated solution—by orchestrating problem framing, customer interviews, synthesis, and experimentation skills into a structured process. Use this to systematically explore problem spaces, validate assumptions, and build confidence before committing to full development—avoiding "build it and they will come" syndrome and ensuring you're solving real customer problems.
This is not a one-time research project—it's a continuous discovery practice that runs in parallel with delivery, typically 1-2 discovery cycles per quarter.
Works best with: Your starting problem hypothesis — even a rough one. Also useful: Prior research, customer access, timeline, and what decision the discovery must inform.
Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it and skip whatever it covers; don't re-ask.
Arriving empty-handed? That works too. The workflow starts at problem framing and helps you construct the hypothesis first.
Example invocation: Run discovery on this hypothesis: SMB admins abandon onboarding because the data-import step requires IT help they don't have.
The discovery process (Teresa Torres, Marty Cagan) is a structured approach to exploring problem spaces and validating solutions before building. It consists of:
When running this workflow as a guided conversation, use workshop-facilitation as the interaction protocol.
It defines:
Other (specify) when useful)This file defines the workflow sequence and domain-specific outputs. If there is a conflict, follow this file's workflow logic.
Use template.md for the full fill-in structure.
This workflow orchestrates 6 phases over 2-4 weeks, using multiple component and interactive skills.
Goal: Define what you're investigating, who's affected, and success criteria.
1. Run Problem Framing Canvas
skills/problem-framing-canvas/SKILL.md (interactive - MITRE)2. Create Formal Problem Statement
skills/problem-statement/SKILL.md (component)3. Define Proto-Personas (If Needed)
skills/proto-persona/SKILL.md (component)4. Map Jobs-to-be-Done (If Needed)
skills/jobs-to-be-done/SKILL.md (component)If YES: Proceed to Phase 2 (Research Planning)
If NO: Gather existing data first:
Goal: Design research approach, recruit participants, prepare interview guide.
1. Prep Discovery Interviews
skills/discovery-interview-prep/SKILL.md (interactive)2. Recruit Participants
3. Schedule Interviews
Goal: Gather qualitative evidence through customer interviews.
1. Conduct Discovery Interviews
skills/discovery-interview-prep/SKILL.md (Problem validation, JTBD, switch interviews, etc.)2. Take Structured Notes
3. Review Support Tickets & Analytics (Parallel)
Saturation = same pain points emerge across 3+ interviews, no new insights
If YES (saturated after 5-7 interviews): Proceed to Phase 4 (Synthesis)
If NO (still learning new things): Schedule 3-5 more interviews
Goal: Identify patterns, prioritize pain points, map opportunities.
1. Affinity Mapping (Thematic Analysis)
2. Create Customer Journey Map (Optional)
skills/customer-journey-mapping-workshop/SKILL.md (interactive)3. Prioritize Pain Points
4. Update Problem Statement
skills/problem-statement/SKILL.md (component)Goal: Explore solution options, design experiments, validate assumptions.
1. Generate Opportunity Solution Tree
skills/opportunity-solution-tree/SKILL.md (interactive)Alternative: Use Lean UX Canvas
skills/lean-ux-canvas/SKILL.md (interactive)2. Design Experiments
3. Run Experiments
If YES (validated): Proceed to Phase 6 (Decide & Document)
If NO (invalidated):
Goal: Commit to build, document decision, communicate to stakeholders.
1. Make Go/No-Go Decision
2. Define Epic Hypotheses (If GO)
skills/epic-hypothesis/SKILL.md (component)3. Write PRD (If GO)
skills/prd-development/SKILL.md (workflow)4. Communicate Findings
Week 1:
├─ Day 1-2: Frame the Problem
│ ├─ skills/problem-framing-canvas/SKILL.md (120 min)
│ ├─ skills/problem-statement/SKILL.md (30 min)
│ └─ [Optional] skills/proto-persona/SKILL.md, skills/jobs-to-be-done/SKILL.md
│
├─ Day 3: Research Planning
│ ├─ skills/discovery-interview-prep/SKILL.md (90 min)
│ ├─ Recruit participants (2-3 days)
│ └─ Schedule 5-10 interviews
│
└─ Day 4-5: Conduct Research (Start)
└─ First 2-3 customer interviews
Week 2:
├─ Day 1-3: Conduct Research (Continue)
│ └─ Remaining customer interviews (3-7 more)
│
├─ Day 4-5: Synthesize Insights
│ ├─ Affinity mapping (120 min)
│ ├─ [Optional] skills/customer-journey-mapping-workshop/SKILL.md (90 min)
│ ├─ Prioritize pain points
│ └─ Update problem statement
│
└─ Decision: Reached saturation? (if NO, +1 week more interviews)
Week 3:
├─ Day 1-2: Generate & Validate Solutions
│ ├─ skills/opportunity-solution-tree/SKILL.md (90 min)
│ └─ Design experiments
│
├─ Day 3-5: Run Experiments
│ ├─ Concierge tests, prototypes, or A/B tests
│ └─ Gather validation data
│
└─ Decision: Validated? (if NO, pivot to next solution, +1-2 weeks)
Week 4:
└─ Decide & Document
├─ Make GO/NO-GO decision
├─ [If GO] skills/epic-hypothesis/SKILL.md (60 min per epic)
├─ [If GO] skills/prd-development/SKILL.md (1-2 days)
└─ Communicate findings (30 min readout)
Total Time Investment:
See examples/sample.md for a full discovery process example.
Mini example excerpt:
**Problem:** Onboarding drop-off due to jargon
**Insight:** 6/10 users quit at step 3
**Decision:** Go with guided checklist experiment
Symptom: Rely only on analytics and support tickets, no qualitative research
Consequence: Miss "why" behind behavior, build wrong solutions
Fix: Always interview 5-10 customers per discovery cycle (even if you have data)
Symptom: "Would you use [feature X] if we built it?"
Consequence: Confirmation bias, customers say "yes" to be polite
Fix: Use Mom Test questions from skills/discovery-interview-prep/SKILL.md (focus on past behavior)
Symptom: Interview 2-3 customers, declare discovery complete
Consequence: Small sample, not representative
Fix: Continue interviews until same patterns emerge across 3+ customers (typically 5-7 interviews minimum)
Symptom: Spend 6 weeks synthesizing insights, never move to solutions
Consequence: No delivery, team loses momentum
Fix: Time-box discovery to 3-4 weeks; after Phase 6, move to execution
Symptom: Run discovery once before building, then stop
Consequence: Miss evolving customer needs, market changes
Fix: Continuous discovery (Teresa Torres): 1 customer interview per week, ongoing
Phase 1:
skills/problem-framing-canvas/SKILL.md (interactive)skills/problem-statement/SKILL.md (component)skills/proto-persona/SKILL.md (component, optional)skills/jobs-to-be-done/SKILL.md (component, optional)Phase 2:
skills/discovery-interview-prep/SKILL.md (interactive)Phase 4:
skills/customer-journey-mapping-workshop/SKILL.md (interactive, optional)Phase 5:
skills/opportunity-solution-tree/SKILL.md (interactive)skills/lean-ux-canvas/SKILL.md (interactive, alternative)Phase 6:
skills/epic-hypothesis/SKILL.md (component)skills/prd-development/SKILL.md (workflow)Skill type: Workflow
Suggested filename: discovery-process.md
Suggested placement: /skills/workflows/
Dependencies: Orchestrates 10+ component and interactive skills across 6 phases
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