Product Manager Toolkit

Overview

This skill provides [TODO: Add 2-3 sentence overview].

Core Value: [TODO: Add value proposition with metrics]

Target Audience: [TODO: Define target users]

Use Cases: [TODO: List 3-5 primary use cases]

Core Capabilities

• [Capability 1] - [Description]

• [Capability 2] - [Description]

• [Capability 3] - [Description]

• [Capability 4] - [Description]

Key Workflows

Workflow 1: [Workflow Name]

Time: [Duration estimate]

Steps:

• [Step 1]

• [Step 2]

• [Step 3]

Expected Output: [What success looks like]

Workflow 2: [Workflow Name]

Time: [Duration estimate]

Steps:

• [Step 1]

• [Step 2]

• [Step 3]

Expected Output: [What success looks like]

Essential tools and frameworks for modern product management, from discovery to delivery. This toolkit provides Python automation tools for prioritization and interview analysis, comprehensive frameworks for decision-making, and battle-tested templates for product documentation.

What This Skill Provides:

• RICE prioritization engine with portfolio analysis

• NLP-based customer interview analyzer

• Complete PRD templates and interview guides

• Discovery frameworks (JTBD, Opportunity Trees)

• Metrics frameworks (North Star, Funnels)

Best For:

• Feature prioritization and roadmap planning

• User research synthesis and insight extraction

• Requirements documentation (PRDs, user stories)

• Discovery planning and stakeholder alignment

Quick Start

Feature Prioritization

python scripts/rice_prioritizer.py sample # Create sample CSV python scripts/rice_prioritizer.py sample_features.csv --capacity 15

Interview Analysis

python scripts/customer_interview_analyzer.py interview_transcript.txt

PRD Creation

• Choose template: Standard, One-Page, Agile Epic, or Feature Brief

• See templates.md for complete formats

• Fill sections based on discovery work

• Review with stakeholders and version control

Core Workflows

1. Feature Prioritization Process

Steps:

• Gather feature requests (customer feedback, sales, tech debt, strategic)

• Score with RICE: python scripts/rice_prioritizer.py features.csv

• Reach: Users affected per quarter

• Impact: massive/high/medium/low/minimal (3x/2x/1x/0.5x/0.25x)

• Confidence: high/medium/low (100%/80%/50%)

• Effort: Person-months

• Analyze portfolio (quick wins vs big bets)

• Generate roadmap with capacity planning

Detailed Methodology: See frameworks.md for RICE, Value vs Effort Matrix, MoSCoW, and Kano Model.

2. Customer Discovery Process

Steps:

• Conduct interviews using semi-structured format

• Analyze insights: python scripts/customer_interview_analyzer.py transcript.txt

• Extracts pain points, feature requests, JTBD, sentiment, themes

• Synthesize findings across interviews

• Validate solutions with prototypes

Interview Scripts: See templates.md for complete discovery and validation interview guides.

Discovery Frameworks: See frameworks.md for Customer Interview Guide, Hypothesis Template, and Opportunity Solution Tree.

3. PRD Development Process

Steps:

• Choose template based on project size:

• 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: Problem → Solution → Success Metrics

• Collaborate with engineering, design, sales, support

Complete Templates: See templates.md for all PRD formats with examples.

Python Tools

rice_prioritizer.py

RICE framework implementation with portfolio analysis and roadmap generation.

Key Features:

• RICE score calculation

• Portfolio balance (quick wins, big bets, fill-ins, time sinks)

• Quarterly roadmap with capacity planning

• Multiple output formats (text/json/csv)

Usage:

Basic prioritization

python3 scripts/rice_prioritizer.py features.csv

With team capacity

python3 scripts/rice_prioritizer.py features.csv --capacity 20

JSON output for tool integration

python3 scripts/rice_prioritizer.py features.csv --output json -f roadmap.json

CSV Format:

name,reach,impact,confidence,effort User Dashboard,500,2,0.8,5 API Rate Limiting,1000,2,0.9,3

Complete Documentation: See tools.md for full options, output formats, and integration patterns.

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 and competitor mentions

Usage:

Analyze interview

python3 scripts/customer_interview_analyzer.py interview.txt

JSON output for research tools

python3 scripts/customer_interview_analyzer.py interview.txt --output json -f analysis.json

Complete Documentation: See tools.md for full capabilities, output formats, and batch analysis workflows.

Reference Documentation

Frameworks (frameworks.md)

Detailed frameworks and methodologies:

• Prioritization: RICE (detailed), Value vs Effort Matrix, MoSCoW, Kano Model

• Discovery: Customer Interview Guide, Hypothesis Template, Opportunity Solution Tree

• Metrics: North Star Framework, Funnel Analysis (AARRR), Feature Success Metrics, Cohort Analysis

Templates (templates.md)

Complete templates and best practices:

• PRD Templates: Standard, One-Page, Agile Epic, Feature Brief

• Interview Guides: Discovery interviews, solution validation

• Best Practices: Writing PRDs, prioritization, discovery, stakeholder management

• Common Pitfalls: What to avoid and how to fix

Tools (tools.md)

Python tool documentation and integrations:

• rice_prioritizer.py: Complete usage, options, output formats

• customer_interview_analyzer.py: Full capabilities and workflows

• Integration Patterns: Jira, ProductBoard, Amplitude, Figma, Dovetail, Slack

• Platform Setup: Step-by-step for each tool

• Troubleshooting: Common issues and solutions

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

See tools.md for detailed integration workflows and platform-specific setup guides.

Quick Commands

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 --output json