# opportunity-solution-trees

Builds an Opportunity Solution Tree that ties one business metric to customer needs, then compares solutions and fast experiments.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 370 installs · ★ 54
- Author: pmprompt
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/pmprompt/claude-plugin-product-management/tree/HEAD/skills/opportunity-solution-trees/SKILL.md
- Updated: 2026-10-22
- HTML: https://affpapa.org/en/nevibecode/skills/opportunity-solution-trees

## What it does

The skill walks you through Teresa Torres's method from Continuous Discovery Habits. At the top sits a single measurable outcome, such as lifting 7-day retention to 40%. Below it are customer opportunities pulled from research, then several solutions per opportunity, and at the bottom experiments that test the riskiest assumptions.

Seven steps run the process: state the outcome, map 3–7 opportunities from interviews and analytics, rank them with the Opportunity Score (importance × [1 − satisfaction]), generate at least three solutions per opportunity, design one or two quick tests with a hypothesis and a success threshold, render the whole tree, and revisit it weekly. Opportunities are written in the customer's voice: "I struggle to…", "I wish I could…".

It falls apart if you skip customer research or the solution is already locked in — the tree turns into drawing practice. The skill also needs input: a metric plus interview, survey, or analytics data. Without them the opportunity step has nothing to stand on, so talk to a few customers first.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add pmprompt/claude-plugin-product-management --skill opportunity-solution-trees -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/opportunity-solution-trees/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/opportunity-solution-trees/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add pmprompt/claude-plugin-product-management --skill opportunity-solution-trees -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/opportunity-solution-trees/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add pmprompt/claude-plugin-product-management --skill opportunity-solution-trees -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/opportunity-solution-trees/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install pmprompt/claude-plugin-product-management opportunity-solution-trees
```

2. **Manually: put the files in place**
- File: `.github/skills/opportunity-solution-trees/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add pmprompt/claude-plugin-product-management --skill opportunity-solution-trees -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/pmprompt/claude-plugin-product-management --path skills/opportunity-solution-trees
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/opportunity-solution-trees/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add pmprompt/claude-plugin-product-management --skill opportunity-solution-trees -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/pmprompt/claude-plugin-product-management/tree/HEAD/skills/opportunity-solution-trees/SKILL.md

## When to use it
- connect a business metric to customer needs
- separate opportunities from feature requests
- compare several solutions for one opportunity
- pick a fast experiment for a risky assumption
- give stakeholders one shared view of priorities

## Example prompts
- build an opportunity solution tree for 7-day retention
- map these interviews into opportunities and solutions the Teresa Torres way
- compare solutions for the need "I struggle to understand my stats"

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 00707e6140995ebf.

BEGIN THIRD-PARTY FILE 00707e6140995ebf
```text
---
name: opportunity-solution-trees
description: Use when asked to "opportunity solution tree", "OST", "Teresa Torres", "map customer opportunities to outcomes", "structure discovery around opportunities", or "compare solutions for a customer need". Helps product teams connect outcomes to customer opportunities and test solutions with Opportunity Solution Trees (created by Teresa Torres).
---

# Opportunity Solution Trees

## Domain Context

The **Opportunity Solution Tree** (Teresa Torres, *Continuous Discovery Habits*) is the backbone of modern product discovery. It prevents teams from jumping to solutions by forcing them to first map the opportunity space.

**Structure (4 levels):**

1. **Desired Outcome** (top) — The measurable business or product outcome you're pursuing. Should be a single, clear metric (e.g., "increase 7-day retention to 40%"). This comes from your OKRs or product strategy.

2. **Opportunities** (second level) — Customer needs, pain points, or desires discovered through research. Frame them from the customer's perspective: "I struggle to..." or "I wish I could..." Prioritize using **Opportunity Score: Importance × (1 − Satisfaction)** (Dan Olsen).

3. **Solutions** (third level) — Possible ways to address each opportunity. Generate multiple solutions per opportunity — don't commit to the first idea. The **Product Trio** (PM + Designer + Engineer) should ideate together.

4. **Experiments** (bottom) — Fast, cheap tests to validate whether a solution addresses the opportunity. Use assumption testing (Value, Usability, Viability, Feasibility).

**Key principles:**
- One outcome at a time — don't try to solve everything
- Opportunities, not features — never let customers design solutions
- Compare and contrast — generate at least 3 solutions per opportunity
- Discovery is not linear — loop back if experiments fail
- Continuous, not periodic — update the tree weekly

## Input Requirements

- A desired outcome or business metric to improve
- Customer research data (interviews, surveys, analytics, feedback)
- Optionally: existing opportunities or solution ideas to organize

## What It Is
```
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