Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsBlogPro
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Authors
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges
  • Chrome Extension
  • Skill Manager

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

ProTermsPrivacyRefunds
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 10/4/2026
ai-agentsgo

Security Analysis

A100/100

Scanned 10/4/2026

$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 automatically 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
Files
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

qa-amanqa-aman
View sourceSee grades on GitHubMore from qa-aman →
SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

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 (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Related Skills

Caveman

Terse caveman voice: answer first, fluff gone, every technical fact kept. Use for /caveman, "caveman mode", "talk like caveman", "be brief", "less tokens". Stays on until "stop caveman" or "normal mode".

1100021 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

698461 votes

Writing Skills

Create and manage Claude Code skills in HASH repository following Anthropic best practices. Use when creating new skills, modifying skill-rules.json, understanding trigger patterns, working with hooks, debugging skill activation, or implementing progressive disclosure. Covers skill structure, YAML frontmatter, trigger types (keywords, intent patterns), UserPromptSubmit hook, and the 500-line rule. Includes validation and debugging with SKILL_DEBUG. Examples include rust-error-stack, cargo-dep...

3931 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3421 votes

catchup

Recovers the conversation and failed tool calls of a previous Codex, Amp, Claude Code, Antigravity, Cline, Copilot CLI, Cursor, DeepSeek Harness, Grok Build, Kimi, OpenCode, Pi Agent, or ZCode session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", asks to recover/summarize a previous session before continuing, or asks to diagnose or report a catchup failure. Do NOT use for the current conversation, git history, or any non-agent log.

741 votes
View all in ai-agents →