product-manager-toolkit
sickn33/agentic-awesome-skills
Essential tools and frameworks for modern product management, from discovery to delivery.
What is product-manager-toolkit?
A comprehensive product management toolkit providing frameworks, scripts, and templates for feature prioritization, customer discovery, and PRD development. Use this when you need to systematize product decisions, analyze customer interviews, or create structured product requirements.
- RICE-based feature prioritization with portfolio balance analysis and quarterly roadmap generation
- NLP-powered customer interview analysis extracting pain points, feature requests, and sentiment
- Multiple PRD templates (Standard, One-Page, Agile Epic, Feature Brief) for different contexts
- Customer discovery frameworks including interview guides, hypothesis templates, and opportunity mapping
- Metrics and analytics templates for North Star identification, funnel analysis, and feature success tracking
- Stakeholder management and prioritization best practices with common pitfall guidance
How to install product-manager-toolkit
npx skills add https://github.com/sickn33/agentic-awesome-skills --skill product-manager-toolkit- Python 3.7+ for running RICE prioritizer and interview analyzer scripts
- Text files or transcripts for interview analysis
- CSV format for feature data (name, reach, impact, confidence, effort)
How to use product-manager-toolkit
- 1.Run `python scripts/rice_prioritizer.py sample` to create a sample CSV template
- 2.Populate your features with reach (users/quarter), impact (massive/high/medium/low/minimal), confidence (high/medium/low), and effort (xl/l/m/s/xs)
- 3.Execute `python scripts/rice_prioritizer.py features.csv --capacity [person-months]` to generate prioritized roadmap
- 4.For customer insights, run `python scripts/customer_interview_analyzer.py transcript.txt` on interview recordings or notes
- 5.Select appropriate PRD template from `references/prd_templates.md` based on feature complexity and timeline
- 6.Collaborate with stakeholders using the provided frameworks (hypothesis template, opportunity solution tree, RACI model)
Use cases
- Prioritize a backlog of 50+ feature requests using RICE scoring to allocate quarterly capacity
- Analyze 10 customer interviews to identify patterns, pain points, and opportunities for product direction
- Create a PRD for a major feature with engineering, design, and sales alignment
- Build a metrics framework to measure success of a new product initiative
- Map customer problems to solution hypotheses using opportunity solution trees
- Product managers building data-driven roadmaps
- Product leaders managing stakeholder alignment and prioritization
- Startup founders validating product-market fit through customer discovery
- Cross-functional teams (engineering, design, sales) collaborating on product strategy
- Teams adopting structured product management processes
product-manager-toolkit FAQ
Standard PRD is comprehensive (11 sections) for major features taking 6-8 weeks; One-Page PRD is concise for smaller features (2-4 weeks); Feature Brief is lightweight for exploration phase (1 week); Agile Epic is sprint-based with user story mapping.
Use estimates and relative comparisons. Reach can be "% of user base," Impact uses the provided scale (Massive/High/Medium/Low/Minimal), Confidence reflects your certainty level, and Effort is person-months. The framework works with rough estimates—consistency matters more than precision.
Yes. Both rice_prioritizer.py and customer_interview_analyzer.py support JSON output format using the `--output json` flag, making it easy to import results into Jira, Asana, Notion, or other tools.
Use the RACI framework included in the toolkit to clarify decision authority. Present prioritization decisions with RICE scores and strategic rationale. The toolkit emphasizes communicating decisions clearly and addressing concerns early.
The toolkit recommends quarterly reviews. This allows you to incorporate new customer feedback, adjust based on actual delivery velocity, and realign with strategic shifts without constant context-switching.
Full instructions (SKILL.md)
Source of truth, from sickn33/agentic-awesome-skills.
name: product-manager-toolkit description: "Essential tools and frameworks for modern product management, from discovery to delivery." risk: critical source: community date_added: "2026-02-27"
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 15
For Interview Analysis
python scripts/customer_interview_analyzer.py interview_transcript.txt
For 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 json
customer_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 json
Reference 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-months
Value 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 permission
Hypothesis 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 D
Metrics & 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 variations
Feature 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 json
When 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.
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