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来源文件:README.md
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║ 77 battle-tested skills + 6 command workflows ║
║ Claude Code • Cursor • Codex • n8n • OpenClaw • and more ... ║
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║ v0.84 • August 10, 2026 • CC BY-NC-SA 4.0 ║
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77 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
Aging products: extend, replace, or retire
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 |
| Lifecycle & EOL | 07-lifecycle-eol-pack.zip | Aging products: extend, replace, or retire — plus the full sunset process |
| All skills | 99-all-skills-pack.zip | All 77 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 77 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 |
| Lifecycle & EOL Suite Summary | The 8-skill lifecycle/sunset suite: the three plays, the EOL chain, and right-sizing |
| Building PM Skills | How raw PM content gets distilled into agent-ready skills |
| START_HERE.md | 60-second onboarding for local repo users |
v0.84 — August 10, 2026 · The Lifecycle & End-of-Life Suite
lifecycle-play-advisor and product-lifecycle-plays diagnose where a product actually sits using seven transition questions, then pick between the three plays — extend, replace, or retire. Includes the seven replacement hazards and a risk register whose contingency column asks the question everyone skips: what is Plan B?eol-readiness-advisor (go/no-go, and it will tell you to hold) → eol-stakeholder-sequence (Legal before Finance before Sales — get the order wrong and you find the landmines after the announcement) → eol-checklist (phase-gated, an owner on every item) → eol-internal-enablement (your teams ready before customers hear) → eol-message (upgraded: three transition paths including the honest no-replacement case) → eol-process (the whole thing, six phases, including the post-EOL review everybody skips)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: lifecycle-play-advisor
argument-hint: "[product that's fading, and what makes you think so]"
description: "Diagnose where a product sits in its lifecycle and which play fits — extend, replace, or retire. Use when a product is fading and you need the call, not just the worry."
intent: >-
Guided triage for a product at the mature-to-decline inflection. Establishes the lifecycle stage
from the transition questions, identifies what is actually driving the pressure, tests the
extension play before conceding to replacement or retirement, and routes to the skill that
executes the chosen play.
type: interactive
theme: product-lifecycle
best_for:
- "Settling an extend-versus-replace-versus-retire argument with a diagnosis instead of volume"
- "Checking whether a product is really in decline or just badly distributed"
- "Finding the cheapest play that actually addresses the pressure"
scenarios:
- "Revenue's been flat for a year and half the team wants a rewrite and half wants to kill it"
- "Leadership says this product is dying — is it, and what should we actually do about it?"
estimated_time: "15-25 min"Work out what to do with a product that has stopped growing. Three plays are available — extend, replace, retire — and this skill gets you to the right one through diagnosis rather than debate, then hands you to whichever skill executes it.
Most teams argue the play before establishing the stage. The argument is unwinnable that way, because nobody has agreed on what's actually happening to the product. Four questions fixes that.
This skill is deliberately willing to say "nothing yet." A mature product throwing off margin with manageable support cost doesn't need a play; it needs to be left alone and watched.
Works best with: The product, and what makes you think something needs to change.
Also useful: Revenue trend and over how long, support load, what customers say, whether an internal driver (cost, capacity, strategy) is really behind the question, and what investment appetite exists.
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 diagnosis runs on questions a PM can answer from what they already know — no report-pulling required. "I don't know" is a valid answer and becomes a labeled assumption in the recommendation.
Example invocations:
Our reporting module has been flat six quarters and people want to rebuild it. Extend, replace, or retire?Leadership wants to kill our parts module. Walk me through whether that's right.And the fourth answer that isn't a play: harvest — stop investing, keep running, set a review date.
The seven transition questions establish stage; the pressure source discriminates the plays. Run both before recommending anything, and show your work — a recommendation the user can audit is one they can defend to someone else.
Default toward the cheapest play that addresses the actual pressure. Extension is under-considered in almost every room, because replacement is more interesting to build and retirement is more decisive to announce. Test extension explicitly, and record why it failed when it does.
ansoff-matrix and organic-growth-advisor.Use workshop-facilitation as the interaction protocol. Give
the heads-up at the start — four questions, about fifteen minutes — and let the user dump context
to skip ahead.
This skill asks up to 4 adaptive questions, then recommends a play with its reasoning, its hazards, and a route out.
Agent asks:
"Which product are we looking at, and what prompted the question? The prompt matters as much as the product — flat revenue, rising support costs, a competitor move, and an exec remark lead to very different diagnoses."
Listen for whether the trigger is internal or external. An internal trigger — manufacturing wants the line, engineering wants to rewrite, finance wants the cost out — is legitimate, but it means the customer-facing case for change is weak and the transition has to be carried entirely by you. Name that early; it changes what the play costs.
Agent asks:
"Let's establish the stage. Seven quick reads — yes or no, gut answers are fine:
Score it:
| Yes count | Stage | Implication |
|---|---|---|
| 0-1 | Mature and healthy | No play needed. Invest or leave alone |
| 2-3 | Mature and softening | Extension territory; watch quarterly |
| 4-5 | Crossing into decline | Pick a play deliberately, now |
| 6-7 | In decline | Replace or retire; extension likely just delays |
Say the count back and name the pattern, not just the number. Yeses clustered on 5 and 6 (channel and price) point somewhere very different from yeses on 3 and 7 (support cost and data) — the first pattern is a distribution problem wearing a product costume.
Agent asks:
"Three sources. Which is loudest?
Pick one as primary, even if two apply."
Why this discriminates:
| Pressure | Points toward | Because |
|---|---|---|
| Demand-side | Extend | The core still solves a real problem for someone — find them |
| Supply/cost-side | Replace | The problem is your economics, not the customer's need |
| Capability-side | Replace or Retire | Depends on whether the need survives the technology |
Name the trap out loud: supply-side pressure arrives at the roadmap disguised as a customer problem. "We need to rebuild this" often means "our costs are bad." That's a legitimate reason for a replacement — but saying it plainly changes what success looks like and who has to carry the transition.
Agent asks:
"Before I recommend anything more expensive, four questions on extending what you have:
Question 4 catches the most expensive misdiagnosis in the set: a healthy product condemned because the distribution channel stopped working or the bundle lost its edge. Fixing the lever is far cheaper than replacing the product — and the broken lever carries straight over to the successor if you don't.
If all four are no, extension is genuinely off the table, and now the user has the "no, because…" on record for when someone asks in three months.
Deliver this structure:
## Lifecycle Play Recommendation: [Product]
**Stage:** [stage] — [n]/7 transition questions, clustered on [which]
**Primary pressure:** [demand / supply-cost / capability] — [evidence]
**Trigger was:** [internal / external] — [what that means for the transition]
### Recommended Play: [Extend / Replace / Retire / Harvest / Nothing yet]
**Because:** [two or three specifics from their answers]
**Extension test:** [passed and how, or failed and why — always state it]
**What this play costs:** [rough shape]
**What you're accepting by choosing it:** [the tradeoff, plainly]
### Hazards to plan for
- [The 2-3 hazards that apply to this play, from the seven]
### Assumptions I made
- [Anything answered "I don't know"]
Then offer numbered next steps:
"Where next?
eol-readiness-advisor
for the go/no-go, or eol-process for the whole thingproduct-lifecycle-plays, especially the seven hazardsorganic-growth-advisor for which
growth path the variant servesproduct-lifecycle-playsPick a number, combine them, or tell me what you'd rather do."
On a Replace recommendation, always add one line: "A replacement is two funded workstreams — a launch and a retirement. If the retirement isn't funded, you've chosen an extension with extra steps."
PM: "Our Parts module has been flat for five quarters. Leadership wants to fold it into the core platform and stop selling it separately."
Agent (Q1): "What prompted it — a customer signal, or an internal one?"
PM: "Internal. It's the smallest line item and someone noticed."
Agent: "Noted — that's an internal trigger, which means there's no customer pressure to help carry a transition. Let's see whether the product agrees with leadership."
Agent (Q2): runs the seven questions. Yeses on 5 (losing money on certain channels) and 6 (bundles losing effectiveness). Everything else no.
Agent: "2 out of 7 — mature and softening, not declining. And the pattern is the interesting part: both of your yeses are on channel and price. Nothing about the product itself came back negative. Support cost is fine, retention is fine."
Agent (Q3): "What's driving the pressure?"
PM: "Honestly? We sell it through the same motion as everything else and it doesn't fit. Reps don't lead with it."
Agent (Q4): extension test. Segment — yes, distributors have asked for a read-only tier. Capability — yes, a read-only view is minor work. Repackage — yes, that's exactly the ask. Channel or product — channel.
Recommendation: Extend, and fix the channel. Stage says mature-softening. Both decline signals sit on distribution and pricing, not the product. A read-only distributor tier addresses a segment that has actively asked, and it's small work. Folding it into the core would have retired a healthy product to solve a sales-motion problem — and the sales-motion problem would have survived the merge.
What you're accepting: a distributor tier means supporting a new buyer type. Small, but not zero.
PM: "Manufacturing wants the NFA-200 line for NFA-500 capacity. So we're retiring the NFA-200."
Agent (Q1): "That's an internal trigger — a capacity constraint, not a customer need. Worth flagging up front: the customer-facing case for change is weak here, so your organization carries the entire transition. What's the revenue trend?"
PM: "Flat four quarters. Service revenue's actually growing."
Agent (Q2): runs the seven. Yeses on 4, 6, 7, and a soft 1. Support costs fine, retention strong, channels profitable.
Agent: "4 out of 7 — mature and softening, not in decline. Your installed base is loyal, under contract, and service margin is healthy. That matters, because it means this isn't a product failing. It's a factory floor you want back."
Agent (Q3): "Primary pressure?"
PM: "Supply side. Manufacturing capacity."
Agent (Q4): extension test. Segment — partially; a modular I/O variant would open bigger jobs. Capability without re-architecture — no, needs a new backplane. Repackage — no, industrial buyers specify on capability. Channel or product — neither.
Agent: "Here's the thing worth saying out loud: the extension your customers would want is the NFA-500. That's a strong signal the replacement play is right — and it raises the question you need to answer before committing. Is the NFA-500 a drop-in for the installed base?"
PM: "...I'd assumed so. I don't actually know."
Recommendation: Replace — with that question as a gate.
Hazards to plan for: internal misalignment (medium), cannibalization (deliberate, low impact), and poor EOL management (high impact) — which is entirely gated on the drop-in question. If the NFA-500 needs different mounting or site work, you don't have a migration path, you have a project, and an EOL date would be a promise you can't keep.
Assumption labeled: drop-in compatibility unverified.
And the line that always goes on a Replace: a replacement is two funded workstreams — a launch and a retirement. Retrofit engineering unfunded means you've chosen an extension with extra steps.
Symptom: The user names a play in their first message and the conversation optimizes it.
Consequence: You've validated an opinion rather than run a diagnosis, and the expensive assumption inside it goes unexamined.
Fix: Run Q2 even when the user arrives certain. It takes two minutes and it either confirms them or saves them a year.
Symptom: "4 out of 7, so you're in decline."
Consequence: Four yeses clustered on channel and price mean something completely different from four on support cost and architecture. The count alone routes people wrong.
Fix: Always name which questions came back yes, and say what that cluster means.
Symptom: "Manufacturing wants the line" becomes "the product should be retired."
Consequence: You run a full retirement when an End of Sale, a price change, or a repackage would have satisfied the actual need more cheaply.
Fix: Name the trigger as internal, then ask what specifically it needs. Often the cheaper move delivers it.
Symptom: The product is clearly dying, so Q4 gets waved through.
Consequence: No written record of why extension failed. In three months someone asks, and the answer is a shrug.
Fix: Ask all four regardless. On a genuinely dead product it takes ninety seconds and produces a defensible "no, because…"
Symptom: Every run produces a play, because producing a play feels like producing value.
Consequence: Healthy mature products get projects they didn't need, funded from budget that had somewhere better to be.
Fix: 0-1 yeses means no play. Say so, set a review date, and stop.
These stand on their own — none is a prerequisite for this skill, and this skill isn't a prerequisite for them.
product-lifecycle-plays — the framework behind this
triage: the strategy grid, the seven hazards, the risk register, the portfolio worksheeteol-readiness-advisor — the retirement play's go/no-goeol-process — running a retirement end to endorganic-growth-advisor — which growth path an extension
servesansoff-matrix — where the next tranche of growth comes fromworkshop-facilitation — the interaction protocol
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