
Product Manager Toolkit
FreeEssential tools for effective product management workflows.
Free · Opens the source repo
What Product Manager Toolkit does
The Product Manager Toolkit is designed to streamline the various aspects of product management, from feature prioritization to customer discovery and PRD development. This toolkit includes essential scripts and templates that help product managers efficiently gather insights, prioritize features, and document requirements. With a focus on practical implementation, it provides a structured approach to managing the product lifecycle, ensuring that teams can effectively align their efforts with strategic goals.
At the core of this toolkit are two key scripts: the RICE Prioritizer and the Customer Interview Analyzer. The RICE Prioritizer allows teams to score and prioritize features based on reach, impact, confidence, and effort, facilitating informed decision-making about which features to develop next. It supports various input formats and generates outputs that can be easily integrated into existing workflows. Meanwhile, the Customer Interview Analyzer helps synthesize user research by extracting key insights from interview transcripts, enabling product teams to identify pain points and feature requests directly from user feedback.
Additionally, the toolkit includes a collection of PRD templates and discovery frameworks that guide product managers through the process of creating clear and actionable product requirement documents. By following the structured workflows provided, teams can ensure thorough planning, effective communication, and continuous iteration based on user feedback. This toolkit is particularly beneficial for product managers looking to enhance their strategic planning and execution capabilities while minimizing common pitfalls in product development.
Overall, the Product Manager Toolkit is an invaluable resource for product teams aiming to improve their processes and outcomes through a systematic approach to product management. By leveraging these tools, product managers can better align their work with user needs and business objectives, leading to more successful product outcomes.
When to use it
Use this toolkit when you need structured frameworks and tools for managing product development processes, particularly in feature prioritization and user research.
When not to use it
This toolkit may not be suitable for teams that require highly customized or niche product management solutions outside the provided frameworks.
What you can build with it
Prioritizing Features for a New Product
Use the RICE Prioritizer to score potential features based on user feedback and strategic goals, ensuring the most impactful features are developed first.
Conducting User Interviews
Utilize the Customer Interview Analyzer to synthesize insights from user interviews, helping to identify common pain points and feature requests.
Creating a Product Requirement Document
Select a suitable PRD template from the toolkit and follow the structured process to draft, review, and finalize your product requirements.
How to install Product Manager Toolkit
View source1. Install with the skills CLI
npx skills add alirezarezvani/claude-skills/product-manager-toolkit --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by alirezarezvaniProduct Manager Toolkit
Essential tools and frameworks for modern product management, from discovery to delivery.
Table of Contents
Quick Start
For Feature Prioritization
# Create sample data file
python scripts/rice_prioritizer.py sample
# Run prioritization with team capacity
python scripts/rice_prioritizer.py sample_features.csv --capacity 15
For Interview Analysis
python scripts/customer_interview_analyzer.py interview_transcript.txt
For PRD Creation
- Choose template from
references/prd_templates.md - Fill sections based on discovery work
- Review with engineering for feasibility
- Version control in project management tool
Core Workflows
Feature Prioritization Process
Gather → Score → Analyze → Plan → Validate → Execute
Step 1: Gather Feature Requests
- Customer feedback (support tickets, interviews)
- Sales requests (CRM pipeline blockers)
- Technical debt (engineering input)
- Strategic initiatives (leadership goals)
Step 2: Score with RICE
# Input: CSV with features
python scripts/rice_prioritizer.py features.csv --capacity 20
See references/frameworks.md for RICE formula and scoring guidelines.
Step 3: Analyze Portfolio
Review the tool output for:
- Quick wins vs big bets distribution
- Effort concentration (avoid all XL projects)
- Strategic alignment gaps
Step 4: Generate Roadmap
- Quarterly capacity allocation
- Dependency identification
- Stakeholder communication plan
Step 5: Validate Results
Before finalizing the roadmap:
- Compare top priorities against strategic goals
- Run sensitivity analysis (what if estimates are wrong by 2x?)
- Review with key stakeholders for blind spots
- Check for missing dependencies between features
- Validate effort estimates with engineering
Step 6: Execute and Iterate
- Share roadmap with team
- Track actual vs estimated effort
- Revisit priorities quarterly
- Update RICE inputs based on learnings
Customer Discovery Process
Plan → Recruit → Interview → Analyze → Synthesize → Validate
Step 1: Plan Research
- Define research questions
- Identify target segments
- Create interview script (see
references/frameworks.md)
Step 2: Recruit Participants
- 5-8 interviews per segment
- Mix of power users and churned users
- Incentivize appropriately
Step 3: Conduct Interviews
- Use semi-structured format
- Focus on problems, not solutions
- Record with permission
- Take minimal notes during interview
Step 4: Analyze Insights
python scripts/customer_interview_analyzer.py transcript.txt
Extracts:
- Pain points with severity
- Feature requests with priority
- Jobs to be done patterns
- Sentiment and key themes
- Notable quotes
Step 5: Synthesize Findings
- Group similar pain points across interviews
- Identify patterns (3+ mentions = pattern)
- Map to opportunity areas using Opportunity Solution Tree
- Prioritize opportunities by frequency and severity
Step 6: Validate Solutions
Before building:
- Create solution hypotheses (see
references/frameworks.md) - Test with low-fidelity prototypes
- Measure actual behavior vs stated preference
- Iterate based on feedback
- Document learnings for future research
PRD Development Process
Scope → Draft → Review → Refine → Approve → Track
Step 1: Choose Template
Select from references/prd_templates.md:
| Template | Use Case | Timeline |
|---|---|---|
| Standard PRD | Complex features, cross-team | 6-8 weeks |
| One-Page PRD | Simple features, single team | 2-4 weeks |
| Feature Brief | Exploration phase | 1 week |
| Agile Epic | Sprint-based delivery | Ongoing |
Step 2: Draft Content
- Lead with problem statement
- Define success metrics upfront
- Explicitly state out-of-scope items
- Include wireframes or mockups
Step 3: Review Cycle
- Engineering: feasibility and effort
- Design: user experience gaps
- Sales: market validation
- Support: operational impact
Step 4: Refine Based on Feedback
- Address technical constraints
- Adjust scope to fit timeline
- Document trade-off decisions
Step 5: Approval and Kickoff
- Stakeholder sign-off
- Sprint planning integration
- Communication to broader team
Step 6: Track Execution
After launch:
- Compare actual metrics vs targets
- Conduct user feedback sessions
- Document what worked and what didn't
- Update estimation accuracy data
- Share learnings with team
Tools Reference
RICE Prioritizer
Advanced RICE framework implementation with portfolio analysis.
Features:
- RICE score calculation with configurable weights
- Portfolio balance analysis (quick wins vs big bets)
- Quarterly roadmap generation based on capacity
- Multiple output formats (text, JSON, CSV)
CSV Input Format:
name,reach,impact,confidence,effort,description
User Dashboard Redesign,5000,high,high,l,Complete redesign
Mobile Push Notifications,10000,massive,medium,m,Add push support
Dark Mode,8000,medium,high,s,Dark theme option
Commands:
# Create sample data
python scripts/rice_prioritizer.py sample
# Run with default capacity (10 person-months)
python scripts/rice_prioritizer.py features.csv
# Custom capacity
python scripts/rice_prioritizer.py features.csv --capacity 20
# JSON output for integration
python scripts/rice_prioritizer.py features.csv --output json
# CSV output for spreadsheets
python scripts/rice_prioritizer.py features.csv --output csv
Customer Interview Analyzer
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 per section
- Theme and quote extraction
- Competitor mention detection
Commands:
# Analyze interview transcript
python scripts/customer_interview_analyzer.py interview.txt
# JSON output for aggregation
python scripts/customer_interview_analyzer.py interview.txt json
Input/Output Examples
→ See references/input-output-examples.md for details
Integration Points
Compatible tools and platforms:
| Category | Platforms |
|---|---|
| Analytics | Amplitude, Mixpanel, Google Analytics |
| Roadmapping | ProductBoard, Aha!, Roadmunk, Productplan |
| Design | Figma, Sketch, Miro |
| Development | Jira, Linear, GitHub, Asana |
| Research | Dovetail, UserVoice, Pendo, Maze |
| Communication | Slack, Notion, Confluence |
JSON export enables integration with most tools:
# Export for Jira import
python scripts/rice_prioritizer.py features.csv --output json > priorities.json
# Export for dashboard
python scripts/customer_interview_analyzer.py interview.txt json > insights.json
Common Pitfalls to Avoid
| Pitfall | Description | Prevention |
|---|---|---|
| Solution-First | Jumping to features before understanding problems | Start every PRD with problem statement |
| Analysis Paralysis | Over-researching without shipping | Set time-boxes for research phases |
| Feature Factory | Shipping features without measuring impact | Define success metrics before building |
| Ignoring Tech Debt | Not allocating time for platform health | Reserve 20% capacity for maintenance |
| Stakeholder Surprise | Not communicating early and often | Weekly async updates, monthly demos |
| Metric Theater | Optimizing vanity metrics over real value | Tie metrics to user value delivered |
Best Practices
Writing Great PRDs:
- Start with the problem, not the solution
- Include clear success metrics upfront
- Explicitly state what's out of scope
- Use visuals (wireframes, flows, diagrams)
- Keep technical details in appendix
- Version control all changes
Effective Prioritization:
- Mix quick wins with strategic bets
- Consider opportunity cost of delays
- Account for dependencies between features
- Buffer 20% for unexpected work
- Revisit priorities quarterly
- Communicate decisions with context
Customer Discovery:
- Ask "why" five times to find root cause
- Focus on past behavior, not future intentions
- Avoid leading questions ("Wouldn't you love...")
- Interview in the user's natural environment
- Watch for emotional reactions (pain = opportunity)
- Validate qualitative with quantitative data
Quick Reference
# Prioritization
python scripts/rice_prioritizer.py features.csv --capacity 15
# Interview Analysis
python scripts/customer_interview_analyzer.py interview.txt
# Generate sample data
python scripts/rice_prioritizer.py sample
# JSON outputs
python scripts/rice_prioritizer.py features.csv --output json
python scripts/customer_interview_analyzer.py interview.txt json
Reference Documents
references/prd_templates.md- PRD templates for different contextsreferences/frameworks.md- Detailed framework documentation (RICE, MoSCoW, Kano, JTBD, etc.)
Frequently asked questions about Product Manager Toolkit
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