learn-discovery

Guide product managers through Opportunity Solution Tree mapping and lean experiment design.

5|2|Updated Mar 27, 2026
One-click install
npx skills add https://github.com/tarunccet/pm-skills --skill learn-discovery
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: learn-discovery
Source: https://github.com/tarunccet/pm-skills/tree/main/pm-guided-learning/skills/learn-discovery
Command: npx skills add https://github.com/tarunccet/pm-skills --skill learn-discovery

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Helps product managers practice continuous discovery by guiding them through realistic interview synthesis, Opportunity Solution Tree mapping, assumption identification, and lean experiment design so they can reduce risky builds and make evidence-based decisions.

Core Features & Use Cases

  • Interactive Socratic mentoring that asks targeted questions, waits for responses, and adapts difficulty based on learner performance.
  • Opportunity Solution Tree (OST) exercises including grouping parent/child opportunities, prioritizing competing opportunities, and connecting choices to desired outcomes.
  • Assumption mapping and experiment design with risk ranking, lean test options (fake-door, concierge, email outreach), and clear success/failure decision rules; useful for practicing onboarding, retention, and feature validation scenarios.
  • Assessment checkpoints with short quizzes after each stage to reinforce correct framing and elevate understanding of desirability, viability, and feasibility distinctions.

Quick Start

Start the module by telling the mentor you want to practice continuous discovery with the TaskFlow scenario.

Frequently Asked Questions about learn-discovery

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

FAQPage Schema
How do I practice continuous product discovery using Opportunity Solution Trees?

You practice continuous product discovery through interactive Socratic mentoring that guides you through mapping interview insights, grouping opportunities, and designing lean experiments using Opportunity Solution Tree exercises.

What is assumption mapping and how does it help validate product features?

Assumption mapping identifies and ranks your riskiest assumptions, distinguishing between desirability, viability, and feasibility to help you design lean experiments and establish clear success or failure decision rules for feature validation.

How do I design lean experiments to test onboarding and retention hypotheses?

Lean experiments for onboarding and retention are designed by selecting test options like fake-door, concierge, or email outreach, paired with explicit success and failure criteria to validate your riskiest assumptions before building.

Can I use this continuous discovery mentoring without external product management tools?

Continuous discovery mentoring requires no external tooling, providing built-in OST templates, adaptive difficulty Socratic prompts, and staged quizzes to simulate product-trio learning sessions entirely on its own.

What is the best way to structure a product trio learning session for feature validation?

A product trio learning session is structured through staged assessment checkpoints, starting with interview synthesis, moving to Opportunity Solution Tree mapping, and finishing with assumption ranking and lean experiment design.

How does Socratic learning adapt difficulty during product discovery exercises?

Socratic learning adapts difficulty by asking targeted questions, waiting for your responses, and evaluating your performance through short quizzes after each discovery stage to reinforce correct framing and elevate understanding.