Product Manager Toolkit
Essential tools and frameworks for modern product management, from discovery to delivery.
Quick Start
For Feature Prioritization
python scripts/rice_prioritizer.py sample # Create sample CSV
python scripts/rice_prioritizer.py sample_features.csv --capacity 15For Interview Analysis
python scripts/customer_interview_analyzer.py interview_transcript.txtFor PRD Creation
- Choose template from
references/prd_templates.md - Fill in sections based on discovery work
- Review with stakeholders
- Version control in your PM tool
Core Workflows
Feature Prioritization Process
- Gather Feature Requests
- Customer feedback - Sales requests - Technical debt - Strategic initiatives
- Score with RICE
# Create CSV with: name,reach,impact,confidence,effort python scripts/rice_prioritizer.py features.csv
- Reach: Users affected per quarter - Impact: massive/high/medium/low/minimal - Confidence: high/medium/low - Effort: xl/l/m/s/xs (person-months)
- Analyze Portfolio
- Review quick wins vs big bets - Check effort distribution - Validate against strategy
- Generate Roadmap
- Quarterly capacity planning - Dependency mapping - Stakeholder alignment
Customer Discovery Process
- Conduct Interviews
- Use semi-structured format - Focus on problems, not solutions - Record with permission
- Analyze Insights
python scripts/customer_interview_analyzer.py transcript.txtExtracts:
- Pain points with severity - Feature requests with priority - Jobs to be done - Sentiment analysis - Key themes and quotes
- Synthesize Findings
- Group similar pain points - Identify patterns across interviews - Map to opportunity areas
- Validate Solutions
- Create solution hypotheses - Test with prototypes - Measure actual vs expected behavior
PRD Development Process
- Choose Template
- Standard PRD: Complex features (6-8 weeks) - One-Page PRD: Simple features (2-4 weeks) - Feature Brief: Exploration phase (1 week) - Agile Epic: Sprint-based delivery
- Structure Content
- Problem → Solution → Success Metrics - Always include out-of-scope - Clear acceptance criteria
- Collaborate
- Engineering for feasibility - Design for experience - Sales for market validation - Support for operational impact
Key Scripts
rice_prioritizer.py
Advanced RICE framework implementation with portfolio analysis.
Features:
- RICE score calculation
- Portfolio balance analysis (quick wins vs big bets)
- Quarterly roadmap generation
- Team capacity planning
- Multiple output formats (text/json/csv)
Usage Examples:
# Basic prioritization
python scripts/rice_prioritizer.py features.csv
# With custom team capacity (person-months per quarter)
python scripts/rice_prioritizer.py features.csv --capacity 20
# Output as JSON for integration
python scripts/rice_prioritizer.py features.csv --output jsoncustomer_interview_analyzer.py
NLP-based interview analysis for extracting actionable insights.
Capabilities:
- Pain point extraction with severity assessment
- Feature request identification and classification
- Jobs-to-be-done pattern recognition
- Sentiment analysis
- Theme extraction
- Competitor mentions
- Key quotes identification
Usage Examples:
# Analyze single interview
python scripts/customer_interview_analyzer.py interview.txt
# Output as JSON for aggregation
python scripts/customer_interview_analyzer.py interview.txt jsonReference Documents
prd_templates.md
Multiple PRD formats for different contexts:
- Standard PRD Template
- Comprehensive 11-section format - Best for major features - Includes technical specs
- One-Page PRD
- Concise format for quick alignment - Focus on problem/solution/metrics - Good for smaller features
- Agile Epic Template
- Sprint-based delivery - User story mapping - Acceptance criteria focus
- Feature Brief
- Lightweight exploration - Hypothesis-driven - Pre-PRD phase
Prioritization Frameworks
RICE Framework
Score = (Reach × Impact × Confidence) / Effort
Reach: # of users/quarter
Impact:
- Massive = 3x
- High = 2x
- Medium = 1x
- Low = 0.5x
- Minimal = 0.25x
Confidence:
- High = 100%
- Medium = 80%
- Low = 50%
Effort: Person-monthsValue vs Effort Matrix
Low Effort High Effort
High QUICK WINS BIG BETS
Value [Prioritize] [Strategic]
Low FILL-INS TIME SINKS
Value [Maybe] [Avoid]MoSCoW Method
- Must Have: Critical for launch
- Should Have: Important but not critical
- Could Have: Nice to have
- Won't Have: Out of scope
Discovery Frameworks
Customer Interview Guide
1. Context Questions (5 min)
- Role and responsibilities
- Current workflow
- Tools used
2. Problem Exploration (15 min)
- Pain points
- Frequency and impact
- Current workarounds
3. Solution Validation (10 min)
- Reaction to concepts
- Value perception
- Willingness to pay
4. Wrap-up (5 min)
- Other thoughts
- Referrals
- Follow-up permissionHypothesis Template
We believe that [building this feature]
For [these users]
Will [achieve this outcome]
We'll know we're right when [metric]Opportunity Solution Tree
Outcome
├── Opportunity 1
│ ├── Solution A
│ └── Solution B
└── Opportunity 2
├── Solution C
└── Solution DMetrics & Analytics
North Star Metric Framework
- Identify Core Value: What's the #1 value to users?
- Make it Measurable: Quantifiable and trackable
- Ensure It's Actionable: Teams can influence it
- Check Leading Indicator: Predicts business success
Funnel Analysis Template
Acquisition → Activation → Retention → Revenue → Referral
Key Metrics:
- Conversion rate at each step
- Drop-off points
- Time between steps
- Cohort variationsFeature Success Metrics
- Adoption: % of users using feature
- Frequency: Usage per user per time period
- Depth: % of feature capability used
- Retention: Continued usage over time
- Satisfaction: NPS/CSAT for feature
Best Practices
Writing Great PRDs
- Start with the problem, not solution
- Include clear success metrics upfront
- Explicitly state what's out of scope
- Use visuals (wireframes, flows)
- Keep technical details in appendix
- Version control changes
Effective Prioritization
- Mix quick wins with strategic bets
- Consider opportunity cost
- Account for dependencies
- Buffer for unexpected work (20%)
- Revisit quarterly
- Communicate decisions clearly
Customer Discovery Tips
- Ask "why" 5 times
- Focus on past behavior, not future intentions
- Avoid leading questions
- Interview in their environment
- Look for emotional reactions
- Validate with data
Stakeholder Management
- Identify RACI for decisions
- Regular async updates
- Demo over documentation
- Address concerns early
- Celebrate wins publicly
- Learn from failures openly
Common Pitfalls to Avoid
- Solution-First Thinking: Jumping to features before understanding problems
- Analysis Paralysis: Over-researching without shipping
- Feature Factory: Shipping features without measuring impact
- Ignoring Technical Debt: Not allocating time for platform health
- Stakeholder Surprise: Not communicating early and often
- Metric Theater: Optimizing vanity metrics over real value
Integration Points
This toolkit integrates with:
- Analytics: Amplitude, Mixpanel, Google Analytics
- Roadmapping: ProductBoard, Aha!, Roadmunk
- Design: Figma, Sketch, Miro
- Development: Jira, Linear, GitHub
- Research: Dovetail, UserVoice, Pendo
- Communication: Slack, Notion, Confluence
Quick Commands Cheat Sheet
# Prioritization
python scripts/rice_prioritizer.py features.csv --capacity 15
# Interview Analysis
python scripts/customer_interview_analyzer.py interview.txt
# Create sample data
python scripts/rice_prioritizer.py sample
# JSON outputs for integration
python scripts/rice_prioritizer.py features.csv --output json
python scripts/customer_interview_analyzer.py interview.txt jsonWhen to Use
This skill is applicable to execute the workflow or actions described in the overview.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.