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GitHub stars License: CC BY-NC-SA 4.0 PRs Welcome Version Claude Code Plugin Skills
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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: competitive-research-snapshot
argument-hint: "[company/product/segment, and the decision it supports]"
description: "Research a competitive landscape with cited snapshots, a comparison matrix, and so-what implications. Use when a product decision needs competitive grounding, not a market report."
intent: >-
Autonomous competitive research as a workflow: search plan, competitor selection, just-enough
research, Fact/Inference/Assumption labels, real URL citations, and next-step options — producing a
stable snapshot schema that battle cards and delta monitors consume and diff.
type: workflow
theme: market-intelligence
best_for:
- "Grounding a positioning, roadmap, or deal-support decision in cited competitive evidence"
- "Creating the baseline snapshot that the competitive intel watch diffs against"
- "Board or exec prep that needs labeled facts instead of confident storytelling"
scenarios:
- "We're rewriting our positioning next sprint — get me a cited read on our top three competitors"
- "Sales keeps losing to one rival; I need evidence on where they're actually strong and weak"
estimated_time: "20-40 min per run"Research a company's competitive landscape using a workflow, not a one-shot answer: search plan → competitor selection → just-enough research → fact/inference labels → real URL citations → next-step options. The output is a decision-support snapshot, not a market report — and because its schema is stable, downstream skills (battle cards, delta monitors) can consume it and diff it. Because it proceeds on labeled assumptions when questions go unanswered, it can run as an agent task or on a schedule; re-run it and diff against the prior snapshot.
Works best with: the company, product, or segment to research, and the decision this research
should support (positioning, roadmap bet, deal support, board prep) — the decision determines what
"just enough" means.
Also useful: known competitors (or explicit permission to identify them), and any prior snapshot
or market-landscape-scan output in session — the skill builds on evidence already gathered rather
than re-researching it.
Input supplied inline with the invocation — text after the skill name, a pasted context dump, or an
appended ARGUMENTS: line — counts as answers already given. Use it against the question budget;
don't re-ask.
Arriving empty-handed? That works too. The skill opens with at most 3 questions (subject, decision, competitors) and proceeds on labeled assumptions if they go unanswered.
Example invocation: Competitive research snapshot on our expense-automation product — decision: which roadmap bet wins Q1. Competitors: [Competitor A], [Competitor B]; find a third if one matters.
autonomous-investigation
contract in full — question budget of 3, search-plan gate, Fact/Inference/Assumption labels, Just
Enough Mode, stable schema, 4-option Final Step.intelligence-collection-disciplines.competitive-intel-watch
diffs the world against this document. Section order never changes.tam-sam-som-calculator;
you need deep intel on one company's strategy and executives →
company-research / company-intel;
the facts are already gathered → go straight to the battle card.# Competitive Research Snapshot
## 1. Scope
**Company/product:** | **Category:** | **Decision supported:** | **Competitors analyzed:**
## 2. Competitor Snapshots
For each competitor, max 5 bullets:
### Competitor: [Name]
- **Positioning:**
- **Relevant capability:**
- **Likely strength:**
- **Likely weakness:**
- **Key source URL:**
## 3. Quick Comparison
| Dimension | Company | Comp 1 | Comp 2 | Comp 3 |
|---|---|---|---|---|
| Target customer | | | | |
| Core use case | | | | |
| Main strength | | | | |
| Main weakness | | | | |
| Evidence quality | | | | |
## 4. So What?
- **3** product strategy implications
- **2** competitive risks
- **2** product opportunities
- **3** assumptions to validate
Each bullet: label, confidence, source URL where relevant.
A copy/paste fill-in version of this schema, with quality checks, lives in template.md.
battle-card-builder)Accept 1, 2, 3, 4, 1 and 2, Verbose Mode, or a custom path.
A competitor snapshot with honest labels (fictional):
Competitor: Ledgerline
- Positioning: "finance automation for mid-market CFOs" — Fact (homepage, Jul 2026)
- Relevant capability: approval-chain builder shipped in May — Fact (release notes)
- Likely strength: ERP integrations; 40+ listed, reviewers confirm the top 5 work well — Fact (G2 reviews)
- Likely weakness: implementation time; complaint cluster across 11 reviews since March — Inference (review mining; no benchmark data)
- Key source URL: pricing page
The "Evidence quality" row doing its job: the comparison matrix rates Comp 3's column low — every claim traces to their own marketing. The So What section then refuses to list Comp 3 as a primary risk: "insufficient independent evidence — Assumption to validate via customer references." That row exists so weak columns can't masquerade as strong ones.
See examples/sample.md for a complete worked snapshot (fictional
FSM-software market) that consumes the market-landscape-scan example and becomes the baseline the
competitive-intel-watch example diffs against. examples/sample-industrial.md
shows the same schema on an industrial evidence diet — filings, registries, and honest
absence-of-evidence.
competitive-intel-watch is for.autonomous-investigation (Workflow) — the governing protocolintelligence-collection-disciplines (Component) — discipline sources and signal chainsmarket-landscape-scan (Workflow) — upstream: surfaces which players deserve this snapshotcompetitive-intel-watch (Workflow) — downstream: diffs future runs against this baselinebattle-card-builder (Workflow) — downstream: turns the snapshot into a field-action cardcompany-research, company-intel — single-company deep divesmarket-intelligence/competitive-research-snapshot-prompt.md in the
https://github.com/deanpeters/product-manager-prompts repo.
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