claude-skills-reference/product-team/CLAUDE.md

Product Team Skills - Claude Code Guidance

This guide covers the 5 production-ready product management skills and their Python automation tools.

Product Skills Overview

Available Skills:

1. product-manager-toolkit/ - RICE prioritization, customer interview analysis (2 tools)
2. agile-product-owner/ - User story generation, sprint planning (1 tool)
3. product-strategist/ - OKR cascade, strategic planning (1 tool)
4. ux-researcher-designer/ - Persona generation, user research (1 tool)
5. ui-design-system/ - Design token generation, component systems (1 tool)

Total Tools: 6 Python automation tools

Python Automation Tools

1. RICE Prioritizer (product-manager-toolkit/scripts/rice_prioritizer.py)

Purpose: RICE framework implementation for feature prioritization

Formula: (Reach × Impact × Confidence) / Effort

Features:

• Portfolio analysis (quick wins vs big bets)
• Quarterly roadmap generation
• Capacity planning (story points or dev days)
• CSV input/output for Jira/Linear integration
• JSON export for dashboards

Usage:

# Basic prioritization
python product-manager-toolkit/scripts/rice_prioritizer.py features.csv

# With capacity planning
python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 20

# JSON output
python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --output json

CSV Format:

feature,reach,impact,confidence,effort
User Dashboard,500,3,0.8,5
API Rate Limiting,1000,2,0.9,3
Dark Mode,300,1,1.0,2

2. Customer Interview Analyzer (product-manager-toolkit/scripts/customer_interview_analyzer.py)

Purpose: NLP-based interview transcript analysis

Features:

• Pain point extraction with severity scoring
• Feature request identification
• Sentiment analysis
• Theme extraction
• Jobs-to-be-done pattern recognition

Usage:

# Analyze transcript
python product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt

# JSON output
python product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt json

3. User Story Generator (agile-product-owner/scripts/user_story_generator.py)

Purpose: INVEST-compliant user story generation

Features:

• Sprint planning with capacity allocation
• Epic breakdown into deliverable stories
• Acceptance criteria generation
• Story point estimation
• Priority scoring

Usage:

# Interactive mode
python agile-product-owner/scripts/user_story_generator.py

# Sprint planning (30 story points)
python agile-product-owner/scripts/user_story_generator.py sprint 30

Output Format:

US-001: As a user, I want to...
Priority: High | Points: 5
Acceptance Criteria:
- Given... When... Then...

4. OKR Cascade Generator (product-strategist/scripts/okr_cascade_generator.py)

Purpose: Automated OKR hierarchy (company → product → team)

Features:

• Alignment scoring (vertical and horizontal)
• Strategy templates (growth, retention, revenue, innovation)
• Key result tracking
• Progress visualization

Usage:

# Growth strategy OKRs
python product-strategist/scripts/okr_cascade_generator.py growth

# Retention strategy
python product-strategist/scripts/okr_cascade_generator.py retention

5. Persona Generator (ux-researcher-designer/scripts/persona_generator.py)

Purpose: Data-driven persona creation from user research

Features:

• Demographic and psychographic profiling
• Goals, pain points, and behavior patterns
• User journey mapping integration
• Empathy map generation

Usage:

# Interactive persona creation
python ux-researcher-designer/scripts/persona_generator.py

# JSON export
python ux-researcher-designer/scripts/persona_generator.py --output json

6. Design Token Generator (ui-design-system/scripts/design_token_generator.py)

Purpose: Complete design token system from brand color

Features:

• Color palette generation (primary, secondary, neutrals)
• Typography scale (font sizes, line heights, weights)
• Spacing system (4px/8px grid)
• Shadow and elevation tokens
• Export formats: CSS, JSON, SCSS

Usage:

# Generate design tokens
python ui-design-system/scripts/design_token_generator.py "#0066CC" modern css

# SCSS output
python ui-design-system/scripts/design_token_generator.py "#0066CC" modern scss

# JSON for Figma integration
python ui-design-system/scripts/design_token_generator.py "#0066CC" modern json

Product Workflows

Workflow 1: Feature Prioritization

# 1. Collect feature requests
cat feature-requests.csv

# 2. Run RICE prioritization
python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 30

# 3. Generate quarterly roadmap

# 4. Create user stories for top priorities
python agile-product-owner/scripts/user_story_generator.py sprint 30

Workflow 2: User Research to Product

# 1. Conduct user interviews

# 2. Analyze transcripts
python product-manager-toolkit/scripts/customer_interview_analyzer.py interview-001.txt

# 3. Generate personas
python ux-researcher-designer/scripts/persona_generator.py

# 4. Create OKRs based on insights
python product-strategist/scripts/okr_cascade_generator.py growth

Workflow 3: Sprint Planning

# 1. Set sprint capacity (story points)
CAPACITY=30

# 2. Generate user stories
python agile-product-owner/scripts/user_story_generator.py sprint $CAPACITY

# 3. Export to Jira (via JSON)
python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --output json > priorities.json

Integration Patterns

Jira Integration

All tools support JSON output for Jira import:

# Export prioritized features
python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --output json > jira-import.json

Figma Integration

Design tokens export for Figma plugins:

# Generate tokens
python ui-design-system/scripts/design_token_generator.py "#0066CC" modern json > design-tokens.json

Confluence Documentation

Use persona generator output for user documentation:

python ux-researcher-designer/scripts/persona_generator.py --output json > personas.json

Quality Standards

All product Python tools must:

• CLI-first design for automation
• Support both interactive and batch modes
• JSON output for tool integration
• Standard library only (minimal dependencies)
• Actionable recommendations

Roadmap

Current (Phase 1): 5 skills deployed with 6 tools

Phase 2 (Q1 2026): Product analytics

• A/B test analyzer
• Funnel conversion tracker
• Cohort retention analyzer

Phase 3 (Q2 2026): Advanced PM tools

• Competitive analysis framework
• Product-market fit assessment
• Revenue impact calculator

See product_team_implementation_guide.md for detailed plans.

Additional Resources

• Implementation Guide: product_team_implementation_guide.md
• Real-World Scenario: REAL_WORLD_SCENARIO.md (if exists)
• Main Documentation: ../CLAUDE.md

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Last Updated: November 5, 2025 Skills Deployed: 5/5 product skills production-ready Total Tools: 6 Python automation tools