Skip to content
Back to skills

Opportunity Solution Tree

ASecurity

Build Opportunity Solution Trees using Teresa Torres' framework for structured product discovery. Use this skill when: - You need to map a desired outcome to opportunities, solutions, and experiments - You want to decide WHAT to build next based on user research and discovery data - You have workshop findings, pilot feedback, or user research to structure into actionable options - You need a visual tree diagram showing the path from outcome to testable experiments

  • 20 stars
  • 0 votes
  • 0 copies
  • 0 views
  • Added October 4, 2026
ai-agentsgo

Security analysis

A100/100

Scanned October 4, 2026

npx -y skills add qa-aman/claude-skills --skill opportunity-solution-tree --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Opportunity Solution Tree?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Opportunity Solution Tree
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/qa-aman-opportunity-solution-tree/badge)](https://www.skillsdirectory.com/skills/qa-aman-opportunity-solution-tree)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: opportunity-solution-tree
description: |
  Build Opportunity Solution Trees using Teresa Torres' framework for structured product discovery. Use this skill when:
  - You need to map a desired outcome to opportunities, solutions, and experiments
  - You want to decide WHAT to build next based on user research and discovery data
  - You have workshop findings, pilot feedback, or user research to structure into actionable options
  - You need a visual tree diagram showing the path from outcome to testable experiments
---

# Opportunity Solution Tree

Interactive skill that builds an OST (Teresa Torres' framework). Maps: Desired Outcome -> Opportunities -> Solutions -> Experiments.

## Workflow

1. **Define outcome** — Ask user, or read from spec success metrics / roadmap goals
2. **Read input data** — Workshop findings, pilot feedback, user research, feedback files
3. **Identify opportunities** — Unmet needs and pain points from the data
4. **Brainstorm solutions** — 2-3 solutions per opportunity
5. **Define experiments** — 1-2 validation experiments per solution
6. **Build tree** — Mermaid diagram + detailed breakdown
7. **Output** — Print to conversation or write to file

## The 4 Levels

### Level 1: Desired Outcome
The measurable business/product outcome.
- Must be specific and measurable: "Increase WAU/MAU ratio by 15%"
- Pull from spec success metrics or roadmap goals
- One tree per outcome

### Level 2: Opportunities
Unmet needs, pain points, desires — NOT solutions.
- Frame as user needs: "Users lose motivation after breaks"
- Or as "How might we..." questions
- Pull from: workshops, feedback, pilot data, persona pain points
- 3-5 opportunities per outcome

### Level 3: Solutions
Feature ideas that address specific opportunities.
- Each solution addresses ONE opportunity
- 2-3 solutions per opportunity (avoid fixating on one idea)
- Can include features already on the roadmap
- Name concretely: "Recovery Mechanic" not "engagement improvement"

### Level 4: Experiments
How to validate each solution before building.
- Types: prototype test, A/B test, user interview, pilot, data analysis, fake door test
- Each experiment has: hypothesis, method, success criteria, effort level
- 1-2 experiments per solution

## Output Format

```markdown
# Opportunity Solution Tree — {Outcome}

**Date:** {DD-MM-YYYY}
**Desired Outcome:** {specific measurable outcome}

## Tree Diagram

```mermaid
graph TD
  O["Outcome: Increase retention by 15%"]
  O --> OP1["Users lose motivation after breaks"]
  O --> OP2["Parents unaware of progress"]
  OP1 --> S1["Recovery mechanic"]
  OP1 --> S2["Progress protection"]
  OP2 --> S3["Parent dashboard"]
  S1 --> E1["Pilot with 50 users"]
  S2 --> E2["User interviews"]
  S3 --> E3["Parent survey"]
```

## Detailed Breakdown

### Opportunity 1: {description}
**Source:** {workshop/feedback/pilot}
**Evidence:** {supporting data}

#### Solution 1a: {name}
- **Description:** {brief}
- **Effort:** Low/Medium/High
- **Experiment:**
  - **Hypothesis:** If we {action}, then {expected result}
  - **Method:** {prototype/interview/pilot/data analysis}
  - **Success Criteria:** {measurable threshold}
  - **Effort:** {days/weeks}

## Priority Matrix

| Solution | Opportunity | Confidence | Effort | Priority |
|----------|------------|-----------|--------|----------|
| {name} | {which} | H/M/L | H/M/L | {1-N} |

## Recommended Next Steps
1. {highest priority experiment to run first}
2. {second priority}
3. {third priority}
```

## Anti-Patterns

- Don't jump to solutions without defining opportunities first
- Don't have only one solution per opportunity — that's not discovery, that's a feature request
- Don't skip experiments — untested solutions are guesses
- Don't define vague outcomes — "improve engagement" is not measurable

## Quality Checklist

- [ ] Outcome is specific and measurable
- [ ] Opportunities are user needs, not solutions in disguise
- [ ] Each opportunity has 2-3 solutions
- [ ] Each solution has at least 1 experiment
- [ ] Mermaid tree diagram is included
- [ ] Priority matrix ranks solutions

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…