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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: incoming-request-advisor
argument-hint: "[paste or describe the incoming message + who sent it]"
description: "Decode an incoming message into a structured breakdown that separates the literal ask from the job-to-be-done. Use before replying to a loaded Slack ping, email, mandate, or escalation."
intent: >-
Act as a chief-of-staff-grade analyst that decodes an incoming message into a structured breakdown, separating the literal ask from the job-to-be-done underneath it, reading sender power and stake from a product leader's chair, and opening the conversation toward a reply or next artifact. Trains the PM habit of finding the outcome before responding.
type: interactive
theme: stakeholder-comms
best_for:
- "Triaging a loaded exec escalation before you fire back a reply"
- "Decoding a vague feature request into the outcome underneath it"
- "Reading power, stake, and subtext in a request from someone senior"
scenarios:
- "My VP just Slacked me 'can we get the dashboard redesign into next sprint?' and I need to read what's really going on"
- "I got a long escalation email from a frustrated customer-success lead and I don't know how to respond"
- "A stakeholder sent a mandate that sounds like a build order and I want the job-to-be-done first"
estimated_time: "5-10 min"Decode an incoming message — a Slack ping, email, mandate, escalation, or FYI — into a structured breakdown before you respond. This skill acts as a chief-of-staff-grade analyst sitting in a product leader's chair: it separates the literal ask from the job-to-be-done underneath it, reads sender power and stake, and opens the conversation toward a reply or next artifact.
Use it when a request lands and your first instinct is to answer the words on the screen. The skill slows that reflex down: it finds the outcome, for whom, and why now — not how to build. It is not a programmer breaking down a spec. When a request sounds like a feature or a build order, the skill hunts for the outcome and the job-to-be-done beneath it.
Works best with: The incoming message itself — pasted text, a screenshot, an image, an attached file, or a PDF. The skill extracts the full message from whatever form it takes before analyzing.
Also useful:
Anything supplied with the invocation itself — text after the skill name, the pasted message, surrounding notes, or an appended ARGUMENTS: line — counts as answers already given. Treat anything written around the message as sender or situation context. Use it and skip whatever it covers; don't re-ask.
Arriving empty-handed? That works too. Drop in the message and nothing else. If sender or situation is unknown and it changes the read, the advisor asks at most 3 targeted questions, one at a time, then proceeds with clearly labeled assumptions. If part of the message is unreadable or cut off, the advisor says so and works with what is there.
Example invocation: My VP DM'd me: "Any chance the dashboard redesign lands next sprint? Board's asking." Analyze this before I reply.
The literal ask is what the words request. The job-to-be-done is the outcome the sender is actually chasing. "Can we get the dashboard redesign into next sprint?" is the ask; "I need something concrete to show the board that we're responsive" may be the job. Responding to the ask when the job is different is how PMs build the wrong thing fast. Every breakdown separates these two explicitly.
Before you respond, you read the room. Who sent it, what is their role relative to your work, and are they upstream (they set your priorities), a peer (they need your cooperation), or downstream (they depend on your output)? Power and stake change the correct response even when the words are identical. A "quick question" from your CEO is not a quick question.
These are not the same thing, and conflating them is a classic PM error:
A deliverable can hit every must-have and still fail the success criteria. Keeping them separate is a core teaching of this skill.
The skill reasons from evidence in the message and marks every guess as an inference. It never presents a guess as a stated fact. Everything inferred lands in an explicit Assumptions to Validate list at the end — so the human knows exactly what the analysis rests on.
The breakdown has twelve sections, but a one-line ping does not need all twelve. The skill collapses or skips empty sections and marks them "none stated" where the template calls for it. Over-filling a trivial message with twelve dense sections is a failure mode, not thoroughness.
Every bullet in the breakdown is 4 to 8 words, ASCII only, short and scannable — as if written on a sticky note. Direct quotes from the message are verbatim and exempt from the length rule.
Use workshop-facilitation as the default interaction protocol for this skill.
It defines:
For this skill specifically: the pasted message is the context dump. Ask clarifying questions only when sender or situation is genuinely unknown and it changes the read — at most 3, one at a time.
Pull the full message from whatever form it arrives in (screenshot, image, file, PDF, or text) before analyzing. If any part is unreadable or cut off, say so and work with what you have.
If sender identity or situation is unknown and it would change the analysis, ask at most 3 targeted questions, one at a time:
Then proceed with clearly labeled assumptions. Do not ask questions the message already answers.
Render in Markdown using the structure below. Scale depth to the message: collapse or skip any empty section; mark it "none stated" where the template calls for it. Apply the Sticky-Note Rule (4–8 word bullets, ASCII only; verbatim quotes exempt). Use template.md for the copy/paste fill-in structure a PM can work through by hand.
## Incoming Request Breakdown
### 1. Classify
- Message type and channel, one line
- Types: meeting prep, feedback, feature request, mandate, escalation, FYI, ask for help, other
### 2. Sender Read
- Who sent it, apparent role
- Relationship: upstream, peer, or downstream
- Power and stake where they matter
### 3. Literal Ask
- What they explicitly want, plain terms
### 4. Underlying Problem Space
- The job they are trying to get done
- The outcome behind the request
- Separate the ask from the need
### 5. Sentiment and Subtext
- Tone, urgency, frustration, enthusiasm, politics
- Quote the tell if there is one
### 6. Must-Haves vs Nice-to-Haves
- Hard requirements for the deliverable
- Soft preferences, clearly separated
### 7. Hard Negatives
- What they explicitly do not want
- "None stated" if none
### 8. Success Criteria
- Pass/fail bar, metric, or definition of done
- How they will judge the result worked
- Capture only what is stated; mark implied ones as inference
- "None stated" if none
### 9. Hard Constraints
- Drop-dead dates, budget, non-negotiables
- "None stated" if none
### 10. Gaps and Ambiguities
- What is unclear or missing before committing
### 11. Risks
- Scope, expectation, political, timeline landmines
### 12. Recommended Next Steps
- 2 to 4 concrete moves, ordered
### Assumptions to Validate
- [Anything inferred rather than stated]
- [Sender read or intent guessed]
- [Success criteria or constraints implied]
After rendering, ask the 1 to 3 sharpest questions you need to sharpen the recommendation, then offer exactly 4 next options:
Ask the user to reply with 1, 2, 3, 4, a combination like 1 and 3, or a custom path.
See examples/conversation-flow.md for a full end-to-end interaction, including message extraction, gap-filling, the rendered breakdown, and the closing options.
Message pasted: "Any chance the dashboard redesign lands next sprint? Board's asking." — from the VP of Product.
Agent output (abridged):
Then: "Is the board meeting date fixed? Do they need working software or a credible plan?" → offers the 4 options, recommends 4 — counter-proposal that protects the outcome (a demoable slice beats an over-committed full redesign).
Message pasted: "Heads up — legal signed off on the new terms." — from a peer PM.
Agent output: Classify (FYI, Slack) + Sender Read + Literal Ask only. Sections 4–11 marked "none stated." Recommended Next Step: acknowledge, file for the launch checklist. No twelve-section wall for a one-liner.
Symptom: Treating a feature-shaped request as a build order and jumping to implementation tasks.
Consequence: You optimize the wrong thing efficiently. You solve the ask and miss the job, then wonder why the sender is still unhappy after you delivered exactly what they said.
Fix: Always run Section 4 (Underlying Problem Space). Name the outcome and the job-to-be-done before touching "how."
Symptom: Listing "the dashboard must have export" under the same heading as "they'll judge this by whether the board is reassured."
Consequence: You build a deliverable that ticks every requirement and still fails the real bar. The two answer different questions — what goes in vs. how they judge it.
Fix: Keep Sections 6 and 8 strictly separate. Ask yourself: is this a thing in the box, or the ruler they measure the box with?
Symptom: Presenting a guess about the sender's motive as if the message stated it.
Consequence: The human acts on fabricated certainty, walks into the room wrong, and loses trust when the assumption cracks.
Fix: Mark every guess as an inference and surface it in Assumptions to Validate. If you didn't read it in the message, it's an assumption — label it.
Symptom: Rendering all twelve sections for a two-sentence FYI.
Consequence: Analysis theater. The reader can't find the signal, and the breakdown looks rigorous while adding nothing.
Fix: Scale depth to the message. Collapse empty sections; mark "none stated." A one-line ping earns a one-paragraph read.
workshop-facilitation — Facilitation protocol for this interactive skill (source of truth)jobs-to-be-done — Deepen the job-to-be-done read surfaced in Section 4stakeholder-mapping — Extend the Sender Read into a full power/stake mapopportunity-solution-tree — Use when option 3 (reframe as discovery framing) is chosenproblem-statement — Turn the Underlying Problem Space into a shareable framing
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