What is the PM Discovery skill?

It is a specialized capability for Claude Code that provides product managers with structured frameworks to synthesize user research and prioritize product roadmaps.

Does this skill help with feature prioritization?

Yes, it includes templates and scoring models for both RICE (Reach, Impact, Confidence, Effort) and ICE (Impact, Confidence, Ease) frameworks.

Can I use this for customer interview preparation?

Absolutely. The skill includes a 'Question Bank' for problem discovery, current solution analysis, and value discovery to guide your user interviews.

What is an Opportunity Solution Tree (OST)?

The OST is a visual framework included in this skill that helps you link business outcomes to customer opportunities, specific solutions, and validation experiments.

When in the development cycle should I use this skill?

It is best used after initial market research but before writing a PRD or starting implementation planning to ensure your product hypothesis is validated.

Product Discovery Toolkit

Name: Product Discovery Toolkit
Author: majesticlabs-dev

bymajesticlabs-dev

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Collaboration Tools

Transforms customer research into actionable product decisions using structured frameworks like JTBD, RICE, and assumption mapping.

About

The Product Discovery Toolkit is a specialized suite of frameworks designed for product managers to bridge the gap between raw research and technical implementation. It provides standardized templates for synthesizing customer interviews, identifying 'Jobs-to-be-Done' (JTBD), and conducting Riskiest Assumption Tests (RAT). By utilizing built-in prioritization models like RICE and ICE scoring, alongside Opportunity Solution Trees, this skill helps teams validate hypotheses and ensure that engineering resources are focused on the most impactful user problems. It is an essential companion for the discovery phase of the product development lifecycle.

Key Features

Comprehensive customer interview synthesis and question banks
Assumption mapping and Riskiest Assumption Test (RAT) frameworks
Opportunity Solution Tree templates to align outcomes with experiments
Jobs-to-be-Done (JTBD) canvases for defining user motivations
Standardized RICE and ICE scoring for objective feature prioritization
13 GitHub stars

Use Cases

Synthesizing qualitative insights into actionable summaries after customer discovery calls
Mapping and testing risky assumptions before committing engineering resources to a new feature
Ranking a product backlog using data-driven RICE scoring to justify roadmap decisions

About

Key Features

Comprehensive customer interview synthesis and question banks
Assumption mapping and Riskiest Assumption Test (RAT) frameworks
Opportunity Solution Tree templates to align outcomes with experiments
Jobs-to-be-Done (JTBD) canvases for defining user motivations
Standardized RICE and ICE scoring for objective feature prioritization
13 GitHub stars

Use Cases

Synthesizing qualitative insights into actionable summaries after customer discovery calls
Mapping and testing risky assumptions before committing engineering resources to a new feature
Ranking a product backlog using data-driven RICE scoring to justify roadmap decisions