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product-manager-toolkit

Automate feature prioritization and customer interview analysis with Python scripts.

Updated Aug 27, 2026
Search Tags:#discovery#interviews#go-to-market#prioritization#RICE#PRD templates
One-click install
npx skills add https://github.com/LPDigital-Agent/galderma-demo-trackwise --skill product-manager-toolkit-lpdigital-agent
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: product-manager-toolkit
Source: https://github.com/LPDigital-Agent/galderma-demo-trackwise/tree/main/.claude/skills/product-manager-toolkit
Command: npx skills add https://github.com/LPDigital-Agent/galderma-demo-trackwise --skill product-manager-toolkit-lpdigital-agent

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Modern product teams juggle prioritization, research synthesis, and documentation across multiple tools. This toolkit consolidates key PM activities into a single, repeatable flow, reducing context-switching and accelerating decision-making.

Core Features & Use Cases

  • RICE prioritization: Score features to balance portfolio with capacity, enabling transparent decision-making.
  • Customer interview analysis: Extract pain points, JTBD, and insights from transcripts to guide product discovery.
  • PRD templates & discovery frameworks: Access standard templates and guided frameworks for problem framing, MVP scopes, and GTM planning.
  • Go-to-market planning & governance: Align discovery outcomes with stakeholders using structured templates and workflows.

Quick Start

  • Run prioritization: python scripts/rice_prioritizer.py features.csv
  • Analyze interviews: python scripts/customer_interview_analyzer.py transcript.txt
  • Explore PRD templates: refer to references/prd_templates.md for formats

Frequently Asked Questions about product-manager-toolkit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate RICE prioritization for a list of product features?▼

You can automate RICE prioritization by running the Python script rice_prioritizer.py with a features.csv file. This scores features to balance portfolio capacity, enabling transparent product decision-making.

What is the best way to extract JTBD and pain points from customer interview transcripts?▼

The best way to extract JTBD and pain points is using the customer_interview_analyzer.py script on a transcript.txt file. This synthesizes research to guide product discovery.

Can I use standard PRD templates and GTM frameworks for MVP planning?▼

Yes, the toolkit provides standard PRD templates and guided frameworks for problem framing, MVP scopes, and go-to-market planning. These are accessible via references to align discovery outcomes with stakeholders.

Do I need Python to run feature scoring and interview analysis workflows?▼

Yes, you need Python to execute the deterministic tooling for feature scoring and interview analysis. The toolkit relies on Python scripts to automate prioritization and research synthesis.

How does a discovery-to-delivery workflow reduce product management decision fatigue?▼

A discovery-to-delivery workflow reduces decision fatigue by consolidating prioritization, research synthesis, and documentation into a single repeatable flow. This minimizes context-switching across multiple tools.

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