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║ 43 battle-tested frameworks for AI agents ║
║ Claude Code • Cowork • Codex • ChatGPT • Gemini ║
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║ v0.4 • Feb 10, 2026 • CC BY-NC-SA 4.0 ║
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Train AI agents to do product management work like a pro.
Frame problems, hunt opportunities, scaffold validation experiments, and kill bad bets fast. With battle-tested frameworks from Teresa Torres, Geoffrey Moore, Amazon, MITRE, and much more from product management's greatest hits.
We found and fixed a facilitation regression in interactive flows.
What happened:
- We expected guided, step-by-step facilitation with progressive context handling.
- In practice, a brevity-focused rewrite path stripped out parts of the original facilitation modality (especially the "walk through questions" behavior).
What we changed in v0.4:
- Standardized a canonical facilitation protocol in
skills/workshop-facilitation/SKILL.md. - Rolled that source-of-truth linkage across interactive skills and facilitation-heavy workflow skills.
- Added mandatory session heads-up,
Context dumpbypass, andBest guessmode. - Added stronger progress labels, interruption handling, and decision-point recommendation rules.
Credit:
- Codex identified the protocol mismatch and implemented the fix across the repo.
Announcement draft: docs/announcements/2026-02-10-v0-4-facilitation-fix.md
Post title: Product Management Skills for Your Agents
Subtitle: Because "just prompt better" is not a strategy.
Still rewriting PM prompts and getting generic AI output? I built a reusable PM Skills repo to help you make sharper decisions, docs, and outcomes faster.
- Full announcement draft:
docs/announcements/2026-02-08-linkedin-launch.md - Substack article draft:
docs/announcements/2026-02-08-substack-savage-launch.md - Announcements index:
docs/announcements/README.md - Skills repo: Product Manager Skills
- Prior prompts repo: Product Manager Prompts
43 ready-to-use PM frameworks that teach AI agents how to do product management work professionally—without you having to explain your process every time.
Instead of saying "Write a PRD" and hoping for the best, the agent already knows:
- ✅ How to structure a PRD
- ✅ What questions to ask stakeholders
- ✅ Which prioritization framework to use (and when)
- ✅ How to run customer discovery interviews
- ✅ How to break down epics using proven patterns
Result: You work faster, with better consistency, at a higher strategic level.
Works with: Claude Code, Cowork, OpenAI Codex, ChatGPT, Gemini, and any AI agent that can read structured knowledge.
Before using any skill:
- Review the skill file and any linked resources. If it includes
scripts/, read them before running. - Prefer least privilege. Skills should not require secrets or network access unless explicitly documented.
- Do a quick dry run with a realistic prompt, then refine
nameanddescriptionfor better discoverability.
Some skills include a scripts/ folder with deterministic helpers for calculations or formatting. These are optional, should be audited before running, and should avoid network calls or external dependencies.
Examples:
skills/tam-sam-som-calculator/scripts/market-sizing.pyskills/user-story/scripts/user-story-template.py
Want to create your own skills? Choose one of these utilities:
scripts/add-a-skill.sh- Content-first, AI-assisted generation from notes/frameworks.scripts/build-a-skill.sh- Guided "build-a-bear" wizard that prompts section-by-section.scripts/find-a-skill.sh- Search skills by name/type/keyword with ranked results.scripts/test-a-skill.sh- Run strict conformance checks and optional smoke checks.scripts/zip-a-skill.sh- Build upload-ready.zipfiles by skill, type, or all skills.
What it does:
- Analyzes your content and suggests skill types
- Generates complete skill files with examples
- Validates metadata for marketplace compliance
- Updates documentation automatically
Usage:
# From a file
./scripts/add-a-skill.sh research/your-framework.md
# Guided wizard
./scripts/build-a-skill.sh
# Find a skill
./scripts/find-a-skill.sh --keyword pricing --type interactive
# Test one skill
./scripts/test-a-skill.sh --skill finance-based-pricing-advisor --smoke
# Build Claude upload zip for one skill
./scripts/zip-a-skill.sh --skill finance-based-pricing-advisor
# Build Claude upload zips for all skills
./scripts/zip-a-skill.sh --all --output dist/skill-zips
# Build Claude upload zips for one category (component|interactive|workflow)
./scripts/zip-a-skill.sh --type component --output dist/skill-zips
# Build curated starter pack
./scripts/zip-a-skill.sh --preset core-pm --output dist/skill-zips
# Show available curated presets
./scripts/zip-a-skill.sh --list-presets
# From clipboard
pbpaste | ./scripts/add-a-skill.sh
# Check available adapters
./scripts/add-a-skill.sh --list-agentsAgent support: Claude Code, Manual mode (works with any CLI), and custom adapters via scripts/adapters/ADAPTER_TEMPLATE.sh
Learn more: See docs/Add-a-Skill Utility Guide.md for complete guide.
Cloning locally? Start with docs/Building PM Skills.md#local-clone-quickstart.
- Keep frontmatter
name<= 64 chars anddescription<= 200 chars. - Ensure the skill folder name matches the
namevalue. - Use
scripts/zip-a-skill.sh --skill <skill-name>(or--type component,--preset core-pm) to generate upload-ready ZIPs. - (Advanced) Use
scripts/package-claude-skills.shif you need unpacked upload-ready folders. - Validate metadata with
scripts/check-skill-metadata.py. - For GitHub ZIP upload flow, see
docs/Using PM Skills with Claude.md.
These 43 skills are organized into three types that build on each other:
┌───────────────────────────────────────────────────────────┐
│ WORKFLOW SKILLS (5) │
│ Complete end-to-end PM processes │
│ Example: "Run a product strategy session" │
│ Timeline: 2-4 weeks │
└───────────────────────────────────────────────────────────┘
↓ orchestrates
┌───────────────────────────────────────────────────────────┐
│ INTERACTIVE SKILLS (19) │
│ Guided discovery with adaptive questions │
│ Example: "Which prioritization framework should I use?" │
│ Timeline: 30-90 minutes │
└───────────────────────────────────────────────────────────┘
↓ uses
┌───────────────────────────────────────────────────────────┐
│ COMPONENT SKILLS (19) │
│ Templates for specific PM deliverables │
│ Example: "Write a user story" │
│ Timeline: 10-30 minutes │
└───────────────────────────────────────────────────────────┘
What: Reusable templates for creating specific PM deliverables (user stories, positioning statements, epics, personas, PRDs, etc.)
When to use: You need a standard template or format for a specific deliverable.
Example: "Write a user story with acceptance criteria" → Use user-story.md
What: Multi-turn conversational flows where AI asks you 3-5 adaptive questions, then offers smart recommendations based on your context.
When to use: You need help deciding which approach to take or gathering context before executing.
Example: "Which prioritization framework should I use?" → Run prioritization-advisor.md, which asks about your product stage, team size, data availability, then recommends RICE, ICE, Kano, or other frameworks.
How they work:
- AI asks 3-5 questions about your context
- You answer (or pick from numbered options)
- AI offers 3-5 tailored recommendations
- You choose one (or combine approaches)
- AI executes using the right component skills
What: Complete PM processes that orchestrate multiple component and interactive skills over days/weeks.
When to use: You need to run a full PM workflow from start to finish (strategy session, discovery cycle, roadmap planning, PRD creation).
Example: "Align stakeholders on product strategy" → Run product-strategy-session.md, which guides you through positioning → problem framing → solution exploration → roadmap planning over 2-4 weeks.
Now that you understand the three types, here's the complete catalog:
| Skill | Use When You Need To... |
|---|---|
| company-research | Deep-dive competitor or company analysis |
| customer-journey-map | Map customer experience across all touchpoints (NNGroup framework) |
| eol-message | Communicate product/feature deprecation gracefully |
| epic-hypothesis | Turn vague initiatives into testable hypotheses with success metrics |
| finance-metrics-quickref | Fast lookup table for 32+ SaaS finance metrics with formulas, benchmarks, and when to use each |
| jobs-to-be-done | Understand what customers are trying to accomplish (JTBD framework) |
| pestel-analysis | Analyze external factors (Political, Economic, Social, Tech, Environmental, Legal) |
| pol-probe | Define lightweight, disposable validation experiments to test hypotheses before building (Dean Peters PoL framework) |
| positioning-statement | Define who you serve, what problem you solve, and how you're different (Geoffrey Moore framework) |
| press-release | Write a future press release to clarify product vision (Amazon Working Backwards) |
| problem-statement | Frame a customer problem with evidence before jumping to solutions |
| proto-persona | Create hypothesis-driven personas before doing full research |
| recommendation-canvas | Document AI-powered product recommendations |
| saas-economics-efficiency-metrics | Evaluate unit economics and capital efficiency (CAC, LTV, payback, margins, burn rate, Rule of 40, magic number) |
| saas-revenue-growth-metrics | Calculate and interpret revenue, retention, and growth metrics (revenue, ARPU, MRR/ARR, churn, NRR, expansion) |
| storyboard | Visualize user journeys with 6-frame narrative storyboards |
| user-story | Write user stories with proper acceptance criteria (Mike Cohn + Gherkin) |
| user-story-mapping | Organize stories by user workflow (Jeff Patton framework) |
| user-story-splitting | Break down large stories using 8 proven patterns |
| Skill | What It Does |
|---|---|
| acquisition-channel-advisor | Evaluate acquisition channels using unit economics, customer quality, and scalability. Recommends scale/test/kill decisions |
| agent-orchestration-advisor | Design multi-agent workflows—break complex tasks into parallel, specialized AI agents. Covers 4 dimensions of orchestration, agent boundary design, launch control tower monitoring, and evaluation frameworks |
| ai-shaped-readiness-advisor | Assess if you're "AI-first" (automating tasks) or "AI-shaped" (redesigning how you work). Evaluates 5 competencies and recommends which to build first |
| business-health-diagnostic | Diagnose SaaS business health using key metrics, identify red flags, and prioritize actions. Analyzes growth, retention, efficiency, and capital health |
| context-engineering-advisor | Diagnose context stuffing (volume without intent) vs. context engineering (structure for attention). Guides memory architecture, retrieval strategies, and Research→Plan→Reset→Implement cycle |
| customer-journey-mapping-workshop | Guides journey mapping with pain point identification |
| discovery-interview-prep | Plans customer interviews (Mom Test style) based on your research goals |
| epic-breakdown-advisor | Splits epics into user stories using Richard Lawrence's 9 patterns |
| feature-investment-advisor | Evaluate feature investments using revenue impact, cost structure, ROI, and strategic value. Delivers build/don't build recommendations |
| finance-based-pricing-advisor | Evaluate pricing changes using financial impact analysis (ARPU/ARPA, conversion, churn risk, NRR, payback) |
| lean-ux-canvas | Sets up hypothesis-driven planning (Jeff Gothelf Lean UX Canvas v2) |
| opportunity-solution-tree | Generates opportunities and solutions, recommends best proof-of-concept to test |
| pol-probe-advisor | Recommends which of 5 prototype types to use based on your hypothesis and risk (Feasibility, Task-Focused, Narrative, Synthetic Data, Vibe-Coded) |
| positioning-workshop | Guides you through defining your positioning with adaptive questions |
| prioritization-advisor | Recommends the right prioritization framework (RICE, ICE, Kano, etc.) for your situation |
| problem-framing-canvas | Leads you through MITRE Problem Framing (Look Inward/Outward/Reframe) |
| tam-sam-som-calculator | Projects market size (TAM/SAM/SOM) with real-world data and citations |
| user-flow-design | Guides you from a problem statement to agent-buildable screen specs with ASCII wireframes, screen registry, and scenario flows |
| user-story-mapping-workshop | Walks you through creating story maps with backbone and release slices |
| workshop-facilitation | Adds one-step-at-a-time facilitation with numbered recommendations for workshop skills |
| Skill | What It Does | Timeline |
|---|---|---|
| discovery-process | Complete discovery cycle: frame problem → research → synthesize → validate solutions | 3-4 weeks |
| prd-development | Structured PRD: problem statement → personas → solution → metrics → user stories | 2-4 days |
| product-strategy-session | Full strategy: positioning → problem framing → solution exploration → roadmap | 2-4 weeks |
| roadmap-planning | Strategic roadmap: gather inputs → define epics → prioritize → sequence → communicate | 1-2 weeks |
| skill-authoring-workflow | Meta workflow: choose add/build path → validate conformance → update docs → package/publish | 30-90 minutes |
Possible skills in development:
- Dangerous Animals of Product Management - Feature hostage negotiations and stakeholder shuttle diplomacy for when you're facing HiPPOs, RHiNOs, and WoLFs (oh my!).
- Pricing for Product Managers - Value-based pricing, packaging strategy, price increases, and grandfather clause negotiations without the panic spiral and flop sweat.
- Classic Business Strategy Frameworks - Ansoff, BCG, Porter's 5 Forces, Blue Ocean, and SWOT in agent-ready format that helps you decide, not decorate slides.
- Storytelling for Product Managers - Narrative arc, demo choreography, and pitch structure built on pro-opera lessons and Hakawati orations for commanding the room.
- Prompt Building for Product Managers - Industrial-strength prompt engineering: team session starters, multi-turn workflow wizards, and reverse engineering templates for artifacts like PRDs.
- Nightmares of Product Management - Telemetry, triage, and tactics for when things don't go as planned: adoption theater, feature graveyards, metric manipulation, launch amnesia, technical debt wildfires. Plus prevention strategies.
Detailed concept notes live in PLANS.md.
Confused by setup options? Start here: PM Skills Rule-of-Thumb Guide.
- Open a conversation with Claude
- Share the skill file: "Read user-story.md"
- Ask Claude to apply it: "Using the User Story skill, write stories for our checkout flow"
cd product-manager-skills
claude "Using the PRD Development workflow, create a PRD for our mobile feature"You can discover via npx skills find <query> and npx skills add deanpeters/Product-Manager-Skills --list, then install for Claude Code. See Using PM Skills with Claude.
Use local workspace paths, GitHub-connected Codex on ChatGPT, or discover/install directly with npx skills. See Using PM Skills with Codex.
Use GitHub app connections (formerly connectors), Custom GPT Knowledge uploads, or Project files. See Using PM Skills with ChatGPT.
Cowork: Import skills as knowledge modules, invoke via natural language. Other agents: Follow your agent's docs for loading custom knowledge.
- Using PM Skills with Claude — Claude Code usage plus GitHub ZIP upload steps for Claude Desktop/Web.
- Using PM Skills with Codex — Local workspace usage plus GitHub-connected Codex on ChatGPT.
- Using PM Skills with ChatGPT — GitHub app connection, Custom GPT Knowledge setup, and Project-based usage.
- PM Skills Rule-of-Thumb Guide — Non-technical setup choices (local repo vs ZIP vs app connections) in plain English.
- Marketplace Strategy — PM-friendly strategy for distributing skills in marketplaces.
- Marketplace Submission Runbook — Step-by-step submission workflow for non-technical teams.
- Marketplace Issue Templates — Reusable issue templates for marketplace execution and tracking.
- PM Tooling Operations Charter — Pedagogic operating stack across M365 Copilot, Codex, ChatGPT, VS Code/Copilot, Cursor, n8n, and Lovable.
- Add-a-Skill Utility Guide — End-to-end automation guide for generating and validating new skills.
- Building PM Skills — How we distill sources into agent-ready PM skills.
→ Workflow: product-strategy-session (2-4 weeks, orchestrates positioning → roadmap)
→ Workflow: discovery-process (3-4 weeks, interviews → synthesis → validation)
→ Interactive: pol-probe-advisor (recommends which prototype type: Feasibility, Task-Focused, Narrative, Synthetic Data, or Vibe-Coded)
→ Component: pol-probe (template for documenting validation experiments)
→ Interactive: ai-shaped-readiness-advisor (assesses 5 competencies: Context Design, Agent Orchestration, Outcome Acceleration, Team-AI Facilitation, Strategic Differentiation)
→ Interactive: context-engineering-advisor (diagnose context stuffing vs. engineering, define boundaries, implement Research→Plan→Reset→Implement cycle)
→ Workflow: prd-development (2-4 days, problem → solution → stories)
→ Workflow: roadmap-planning (1-2 weeks, epics → prioritization → sequencing)
→ Interactive: prioritization-advisor (asks questions, recommends RICE/ICE/Kano)
→ Interactive: epic-breakdown-advisor (Richard Lawrence's 9 patterns)
→ Component: user-story (template + examples)
| Prompts | Skills |
|---|---|
| One-time instructions per task | Reusable frameworks learned once |
| "Write a PRD for X" | Agent knows PRD structure, asks smart questions, handles edge cases |
| You repeat yourself constantly | Agent remembers best practices |
| Inconsistent outputs | Consistent, professional results |
Skills = Less explaining, more strategic work.
Built on proven methods from Geoffrey Moore, Jeff Patton, Teresa Torres, Amazon, Richard Lawrence, MITRE, and more.
Based on decades of PM consulting across healthcare, finance, manufacturing, and tech.
Optimized for AI comprehension—not blog posts, not books, not courses. Executable frameworks.
Every word earns its keep. No filler, no buzzwords, no generic advice.
Shows both "good" and "bad" examples so you know what works and what to avoid.
Every skill follows the same format:
## Purpose
What this skill does and when to use it.
## Key Concepts
Core frameworks, definitions, anti-patterns.
## Application
Step-by-step instructions (with examples).
## Examples
Real-world cases (good and bad).
## Common Pitfalls
What to avoid and why.
## References
Related skills and external frameworks.
Clean. Practical. Zero fluff.
Found a gap? Have a PM framework you'd like to see included?
Ways to contribute:
- Open an issue with your suggestion
- Submit a pull request (we'll help you format it)
- Share feedback on what's working or missing
See CONTRIBUTING.md for detailed guidelines.
Principles:
- Outcome-driven over output-driven (solve problems, don't just ship features)
- Evidence over vibes (validate with data, not opinions)
- Clarity beats completeness (simple and usable beats comprehensive and confusing)
- Examples beat explanations (show, don't just tell)
No hype. No buzzwords. Just frameworks that work.
- Product Manager Prompts — Task-specific prompts for ChatGPT, Claude, Gemini
- Productside — AI-powered product management training and consulting
- Dean's LinkedIn — Essays on AI-amplified product work
CC BY-NC-SA 4.0 — non-commercial use with share-alike.
See LICENSE for full details.
- GitHub Issues: Report bugs or suggest features
- LinkedIn: Connect with Dean Peters
- Productside: Learn more about AI PM consulting
v0.4 — February 10, 2026
Highlights in this release:
- Fixed a facilitation protocol regression where brevity-focused rewrites could remove expected guided-question behavior
- Promoted
workshop-facilitationto canonical source of truth for interactive facilitation - Added consistent opening heads-up, context-dump bypass path, and best-guess mode
- Applied protocol linkage across interactive skills and facilitation-heavy workflow skills
v0.3 — February 9, 2026
Highlights in this release:
- 43 total skills, including Phase 7 finance skills and the new
skill-authoring-workflow - New skill tooling:
add-a-skill,build-a-skill,find-a-skill,test-a-skill,zip-a-skill - New onboarding docs for Claude, Codex, ChatGPT, and non-technical "rule-of-thumb" setup
Built by Dean Peters (Principal Consultant and Trainer at Productside.com) with Anthropic Claude and OpenAI Codex.
Helping product managers work smarter with AI.