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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: user-story
argument-hint: "[feature or user need]"
description: Create user stories with Mike Cohn format and Gherkin acceptance criteria. Use when turning user needs into development-ready work with clear outcomes and testable conditions.
intent: >-
Create clear, concise user stories that combine Mike Cohn's user story format with Gherkin-style acceptance criteria. Use this to translate user needs into actionable development work that focuses on outcomes, ensures shared understanding between product and engineering, and provides testable success criteria.
type: component
theme: pm-artifacts
best_for:
- "Writing user stories with proper acceptance criteria"
- "Converting requirements into development-ready stories"
- "Establishing story quality standards across your team"
scenarios:
- "I need to write a user story for a new notification system in our B2B SaaS app"
- "Convert this PRD requirement into a properly formatted user story with Gherkin acceptance criteria"
estimated_time: "5-10 min"Create clear, concise user stories that combine Mike Cohn's user story format with Gherkin-style acceptance criteria. Use this to translate user needs into actionable development work that focuses on outcomes, ensures shared understanding between product and engineering, and provides testable success criteria.
This is not a feature spec—it's a conversation starter that captures who benefits, what they're trying to do, why it matters, and how you'll know it works.
Works best with: The feature or user need the story captures. Also useful: The user role, the outcome they want, and edge cases the acceptance criteria must cover.
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 skill asks who the user is and what they're trying to accomplish before drafting story and Gherkin criteria.
Example invocation: Write user stories for password reset via SMS for our banking app — include the lockout edge case.
A user story combines:
Use Case (Mike Cohn format):
Acceptance Criteria (Gherkin format):
skills/user-story-splitting/SKILL.md)Before writing a story, ensure you have:
skills/proto-persona/SKILL.md)skills/problem-statement/SKILL.md)If missing context: Run discovery interviews or problem validation work first.
If you want a consistent Markdown stub, you can generate one from CLI inputs. This script is deterministic and does not fetch data or write files.
python3 scripts/user-story-template.py --persona \"trial user\" --action \"log in with Google\" --outcome \"access the app without creating a new password\"
Use template.md for the full fill-in structure.
Fill in the template:
### User Story [ID]:
- **Summary:** [Brief, memorable title focused on value to the user]
#### Use Case:
- **As a** [user name if available, otherwise persona, otherwise role]
- **I want to** [action user takes to get to outcome]
- **so that** [desired outcome]
Quality checks:
Common mistakes:
Fill in the template:
#### Acceptance Criteria:
- **Scenario:** [Brief, human-readable scenario describing value]
- **Given:** [Initial context or precondition]
- **and Given:** [Additional context or preconditions]
- **and Given:** [Additional context as needed]
- **and Given:** [UI-focused context ensuring 'When' can happen]
- **and Given:** [Outcomes-focused context ensuring 'Then' is delivered]
- **When:** [Event that triggers the action—aligns with 'I want to']
- **Then:** [Expected outcome—aligns with 'so that']
Quality checks:
Red flags:
skills/user-story-splitting/SKILL.md)Write a short, memorable summary that captures the story's value:
- **Summary:** [Brief, human-readable title]
Examples:
skills/user-story-splitting/SKILL.mdSee examples/sample.md for full examples (good, bad, and split-needed stories).
Mini example excerpt:
### User Story 042:
- **Summary:** Enable Google login for trial users to reduce signup friction
#### Use Case:
- **As a** trial user visiting the app for the first time
- **I want to** log in using my Google account
- **so that** I can access the app without creating and remembering a new password
#### Acceptance Criteria:
- **Scenario:** First-time trial user logs in via Google OAuth
- **Given:** I am on the login page
- **and Given:** I have a login account
- **When:** I click the "Sign in with Google" button and authorize the app
- **Then:** I am logged into the app and redirected to the onboarding flow
Symptom: "As a developer, I want to refactor the API, so that the code is cleaner"
Consequence: This is an engineering task, not a user story. No user value is delivered.
Fix: If there's no user outcome, it's not a user story—use an engineering task or tech debt ticket instead.
Symptom: Every story starts with "As a user"
Consequence: No persona clarity. Different users have different needs.
Fix: Use specific personas: "As a trial user," "As a paid subscriber," "As an admin," etc. (reference skills/proto-persona/SKILL.md)
Symptom: "I want to click the save button, so that I can save my work"
Consequence: No insight into why the user cares. Just restating the action.
Fix: Dig into the motivation: "so that I don't lose my progress if the page crashes" (real outcome).
Symptom: Acceptance criteria with 5 "When" statements and 5 "Then" statements
Consequence: Story is too big. Likely multiple features bundled together.
Fix: Split the story using skills/user-story-splitting/SKILL.md. Each When/Then pair should be its own story (or at least evaluated for splitting).
Symptom: "Then the user has a better experience" or "Then it's faster"
Consequence: QA can't verify success. Ambiguous definition of "done."
Fix: Make it measurable: "Then the page loads in under 2 seconds" or "Then the user sees a success confirmation message."
skills/user-story-splitting/SKILL.md — How to break large stories into smaller onesskills/proto-persona/SKILL.md — Defines the "As a [persona]" sectionskills/problem-statement/SKILL.md — Stories should address validated problemsskills/epic-hypothesis/SKILL.md — Epics decompose into user storiesskills/user-story/scripts/user-story-template.py — Deterministic Markdown stub generator (no network access)prompts/user-story-prompt-template.md in the https://github.com/deanpeters/product-manager-prompts repo.Skill type: Component
Suggested filename: user-story.md
Suggested placement: /skills/components/
Dependencies: References skills/proto-persona/SKILL.md, skills/problem-statement/SKILL.md
Used by: skills/user-story-splitting/SKILL.md, skills/epic-hypothesis/SKILL.md
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