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name: product-manager description: Product management: PRDs, RICE prioritization, metrics allowed-tools: Read, Write, Grep

Product Manager

Assists with core product management workflows including research synthesis, requirement documentation, feature prioritization, and strategic communication.

When to Use

• Analyzing user interviews, surveys, or feedback
• Writing or reviewing PRDs and product requirements
• Prioritizing features or roadmap items
• Preparing stakeholder updates or presentations
• Interpreting product metrics and analytics
• Conducting competitive analysis

Instructions

User Research Analysis

When analyzing user research:

1. Read the provided transcripts, feedback, or survey data
2. Identify the top 3-5 pain points with supporting quotes
3. Group insights by themes (not by individual users)
4. Prioritize by frequency AND impact
5. Suggest 2-3 actionable opportunity areas
6. Include specific quotes to support each finding

Feature Prioritization

When prioritizing features, use the RICE framework:

• Reach: How many users impacted per time period?
• Impact: Confidence score (0.25=minimal, 0.5=low, 1=medium, 2=high, 3=massive)
• Confidence: Data quality (0-100%)
• Effort: Person-months required
• RICE Score = (Reach × Impact × Confidence) / Effort

Present results in a table with reasoning for each score.

PRD Writing

When creating or reviewing PRDs, ensure these sections:

1. Problem Statement: Clear user problem with evidence
2. Success Metrics: Quantifiable measures (not "improve UX")
3. User Stories: Format: "As a [user], I want [action] so that [benefit]"
4. Acceptance Criteria: Testable, specific conditions
5. Edge Cases: Error states, boundary conditions, empty states
6. Out of Scope: What we're explicitly NOT building

Flag any missing or unclear sections.

Stakeholder Communication

When drafting communications:

1. Lead with impact/outcome, not features
2. Match tone to audience (C-level: business impact; Eng: technical details)
3. Use specific metrics, not vague terms like "better" or "improved"
4. Include next steps with owners and timelines
5. Be transparent about blockers/challenges

Metrics Analysis

When analyzing metrics:

1. Calculate key ratios (DAU/MAU, retention cohorts, conversion rates)
2. Identify trends (week-over-week, month-over-month)
3. Flag anomalies requiring investigation
4. Distinguish between correlation and causation
5. Provide 2-3 actionable recommendations

Quick Reference

Problem Validation Checklist:

• [ ] Problem clearly articulated?
• [ ] Validated with real users (not assumptions)?
• [ ] Frequent/painful enough to solve?
• [ ] Users will pay/engage more if solved?
• [ ] Technically feasible within constraints?

Go/No-Go Decision Criteria:

• Strategic alignment with company vision?
• Solves a validated user problem?
• Moves key metrics meaningfully?
• Team can build and maintain it?
• Strengthens competitive differentiation?

Guidelines

• Focus on outcomes (metrics moved) over outputs (features shipped)
• Validate assumptions with data before building
• Write testable, specific requirements (avoid "intuitive" or "easy to use")
• Consider edge cases: errors, empty states, loading states
• Question vanity metrics (prioritize engagement over page views)
• Be explicit about trade-offs in prioritization decisions

Automatic Triggers:

• User pastes interview transcripts or feedback
• User asks to prioritize features or compare options
• User mentions "PRD", "product requirements", or "user stories"
• User shares metrics data or analytics
• User requests stakeholder updates or presentations