opportunity-solution-tree

Builds Opportunity Solution Trees mapping outcomes to opportunities, solutions, and experiments.

11|Updated Mar 20, 2026
One-click install
npx skills add https://github.com/qa-aman/next-leap-claude-code --skill opportunity-solution-tree-qa-aman
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: opportunity-solution-tree
Source: https://github.com/qa-aman/next-leap-claude-code/tree/main/.claude/skills/opportunity-solution-tree
Command: npx skills add https://github.com/qa-aman/next-leap-claude-code --skill opportunity-solution-tree-qa-aman

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Product teams often jump straight to feature ideas without structuring discovery work, leading to roadmap decisions based on guesses rather than validated user needs. This Skill applies Teresa Torres' Opportunity Solution Tree framework to connect a measurable outcome to opportunities, solutions, and validation experiments. ## Core Features & Use Cases - Structured Discovery Mapping: Builds a four-level tree from desired outcome through opportunities, solutions, and experiments, with a Mermaid diagram for visualization. - Research Synthesis: Reads workshop findings, pilot feedback, user interviews, and persona pain points to identify 3-5 opportunities per outcome. - Prioritization Output: Produces a priority matrix ranking solutions by confidence and effort, plus recommended next experiments to run. - Use Case: After a user research sprint reveals retention issues, use this Skill to map the outcome "increase retention by 15%" to opportunities like "users lose motivation after breaks", generate 2-3 solutions per opportunity, and define validation experiments for each. ## Quick Start Ask the assistant to build an opportunity solution tree for your target outcome using the research and feedback files in this repository.

Frequently Asked Questions about opportunity-solution-tree

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

FAQPage Schema
How do I build an opportunity solution tree from user research?▼

Start with a specific measurable outcome, then extract unmet user needs from interviews, feedback, or workshop data as opportunities. Generate 2-3 solutions per opportunity and define 1-2 validation experiments per solution, then render the result as a Mermaid diagram with a priority matrix.

What is the difference between an opportunity and a solution in Teresa Torres' framework?▼

An opportunity is an unmet user need, pain point, or desire, such as "users lose motivation after breaks". A solution is a concrete feature idea addressing one opportunity, such as a "recovery mechanic". Framing opportunities as solutions in disguise is a common anti-pattern.

How many solutions should each opportunity have in an opportunity solution tree?▼

Each opportunity should have 2-3 distinct solutions. Having only one solution per opportunity turns discovery into a feature request rather than genuine option exploration, which the framework explicitly warns against.

What types of experiments validate solutions before building them?▼

Common experiment types include prototype tests, A/B tests, user interviews, pilots, data analysis, and fake door tests. Each experiment should define a hypothesis, method, measurable success criteria, and effort estimate.

When should I not use an opportunity solution tree?▼

Avoid it when the outcome is vague or unmeasurable, such as "improve engagement", since the tree requires one specific measurable outcome. It is also a poor fit when the decision is already made and no genuine discovery or option comparison is needed.