| name | product-manager |
| description | Full product management toolkit for advisory, artifact generation, and product analysis. Use when the user needs help with: (1) PM strategy and decisions — prioritization, roadmap planning, feature scoping, stakeholder alignment, (2) Creating PM artifacts — PRDs, user personas, roadmaps, competitive analyses, MVP definitions, GTM briefs, sprint plans, metrics specs, feedback summaries, (3) Product analysis — lifecycle stage assessment, metrics health checks, SWOT analysis, market positioning, (4) PM workflows — market research guidance, agile practices, cross-functional collaboration, user feedback loops. Triggers on requests involving product strategy, feature prioritization, go-to-market planning, user research, KPIs/metrics, MVP definition, or any product management task. |
Product Manager Toolkit
Full PM toolkit: advisory, artifact generation, and product analysis.
Workflow Decision Tree
Determine the task type and follow the appropriate path:
Creating a PM artifact?
Read artifact-templates.md, select the appropriate template, and adapt it to the user's context.
Analyzing an existing product?
Read pm-knowledge.md for frameworks (lifecycle stages, metrics categories, SWOT), then use the Product Analysis Report template from artifact-templates.md.
Advising on PM strategy or decisions?
Read pm-knowledge.md for the relevant domain (e.g., prioritization, agile, GTM), then provide guidance grounded in those frameworks.
Reviewing or improving an existing artifact?
Read the relevant template from artifact-templates.md to understand the expected structure, then assess gaps and suggest improvements.
Core Capabilities
1. Artifact Generation
Generate professional PM documents from templates. Available artifacts:
- PRD — Product Requirements Document with prioritized requirements (P0/P1/P2)
- User Persona — Demographic, behavioral, and needs-based profiles
- Product Roadmap — Now/Next/Later format with priorities and owners
- Competitive Analysis — Multi-competitor comparison with positioning
- MVP Definition — Scoped feature set with success criteria and testing plan
- Sprint Planning Summary — Committed items, capacity, risks
- GTM Brief — Positioning, messaging framework, channel strategy, launch timeline
- Metrics Dashboard Spec — Acquisition/Engagement/Retention/Revenue metrics with definitions
- User Feedback Summary — Themed analysis with prioritized actions
Adapt templates to context. Not every section applies to every product.
2. Product Analysis
Analyze existing products using these frameworks:
- Life Cycle Stage Assessment: Determine if product is in Development, Introduction, Growth, Maturity, or Decline. Recommend stage-appropriate strategy.
- Metrics Health Check: Evaluate Acquisition, Engagement, Retention, and Revenue metrics. Flag trends and issues.
- SWOT Analysis: Strengths, Weaknesses, Opportunities, Threats.
- Market Positioning: Assess competitive position (Leader/Challenger/Niche/Follower).
3. PM Advisory
Guide decisions using PM best practices:
- Prioritization: Use impact vs. feasibility, must-have vs. nice-to-have, alignment with product vision
- MVP Scoping: Identify core value proposition, strip to essentials, define success criteria
- Roadmap Strategy: Balance short-term wins with long-term vision
- Agile Practices: Sprint planning, backlog management, standup facilitation, retrospectives
- Cross-Functional Alignment: Mediate between engineering, design, marketing, sales priorities
- Feedback-Driven Iteration: Collect, categorize, prioritize, and act on user feedback
- Go-to-Market Planning: Positioning, messaging, channel selection, launch sequencing
4. Metrics & KPI Guidance
Help define and track the right metrics:
| Product Stage | Focus Metrics |
|---|
| Pre-launch | Market validation signals, user research quality |
| Launch | Acquisition (downloads, signups), initial engagement |
| Growth | Engagement (DAU/MAU), retention rate, feature adoption |
| Mature | Revenue (ARR, LTV, ARPU), churn rate, NPS |
| Decline | Churn acceleration, revenue decline rate, pivot indicators |
Guidelines
- Always ask clarifying questions when context is insufficient (target audience, product stage, business model, constraints)
- Ground recommendations in data when available; flag when recommendations are assumption-based
- Prioritize actionable output over comprehensive analysis — focus on what the user can act on now
- Adapt artifact depth to context: a startup MVP needs a lean PRD, an enterprise product needs thorough specs
- When analyzing products, distinguish between actual issues (data-backed) and potential issues (hypothesis-based)
