How do I install the Opportunity Solution Tree skill?

Run npx skillmds@latest add nandanosql/opportunity-solution-tree in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Opportunity Solution Tree free to use?

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Who published Opportunity Solution Tree?

nandanosql (@nandanosql) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Opportunity Solution Tree by nandanosql

Name: Opportunity Solution Tree
Author: nandanosql

File contents

Purpose

Structure product decisions using Teresa Torres' Opportunity Solution Tree — a visual hierarchy that connects business outcomes to customer opportunities to potential solutions to validation experiments. Prevents teams from jumping to solutions before understanding the opportunity space.

Key Concepts

The Tree Structure

                    OUTCOME
                 (Business goal)
                /       |       \
        Opportunity  Opportunity  Opportunity
       (Customer need/pain point)
        /        \         |
   Solution  Solution   Solution
   (Ideas to address opportunity)
    /     \
Experiment Experiment
(Cheapest way to test)

Rules

Outcomes are business results you're trying to drive (from OKRs)
Opportunities are customer needs, pain points, or desires (from discovery)
Solutions are ideas for addressing opportunities (brainstormed)
Experiments are the cheapest way to test if a solution works
Always compare 3+ solutions per opportunity before picking one

Application

Step 1: Define the Outcome

**Desired Outcome:** [From OKR — e.g., "Increase 7-day activation from 28% to 55%"]
**Why this outcome:** [Connection to business strategy]

Step 2: Map Opportunities

**Opportunities (customer needs that, if addressed, would drive the outcome):**

1. [Opportunity 1 — e.g., "Users don't understand core value during trial"]
   - Evidence: [Interview quotes, data]
   - Size: [# users affected]

2. [Opportunity 2 — e.g., "Data connection step is too technical"]
   - Evidence: [Drop-off data]
   - Size: [# users affected]

3. [Opportunity 3]

Step 3: Generate Solutions (3+ per opportunity)

**Solutions for Opportunity 1:**
| Solution | Effort | Confidence | Notes |
|----------|--------|-----------|-------|
| [Solution A] | [S/M/L] | [H/M/L] | [Rationale] |
| [Solution B] | [S/M/L] | [H/M/L] | [Rationale] |
| [Solution C] | [S/M/L] | [H/M/L] | [Rationale] |

Step 4: Design Experiments

**Experiment for [chosen solution]:**
- **Type:** [Prototype test / Fake door / A/B test / Concierge]
- **What we'll learn:** [Specific question]
- **Success criteria:** [Metric + threshold]
- **Duration:** [Days/weeks]
- **Cost:** [Effort to run]

Quality Rubric

Dimension	0	1	2
Outcome	Not defined	Vague goal	Measurable from OKR
Opportunities	Assumed	Listed from intuition	Evidence-backed from research
Solution Diversity	1 solution (pet idea)	2 solutions	3+ solutions compared
Experiments	None (just build it)	High-cost experiment	Cheapest test possible
Evidence	All assumption	Some data	Research-backed at each level

References

Related Skills

skills/strategy/okr-framework/SKILL.md — Outcome comes from OKRs
skills/discovery/problem-statement/SKILL.md — Opportunities from validated problems
skills/growth/ab-test-design/SKILL.md — Experiment design

External Frameworks

Teresa Torres, Continuous Discovery Habits (2021)

Skill type: Component Domain: Specification & Design

---name: opportunity-solution-treedescription: Structure product decisions using Teresa Torres' Opportunity Solution Tree — connecting outcomes to opportunities to solutions to experiments in a visual hierarchy.---## PurposeStructure product decisions using Teresa Torres' **Opportunity Solution Tree** — a visual hierarchy that connects business outcomes to customer opportunities to potential solutions to validation experiments. Prevents teams from jumping to solutions before understanding the opportunity space.---## Key Concepts### The Tree Structure``` OUTCOME (Business goal) / | \ Opportunity Opportunity Opportunity (Customer need/pain point) / \ | Solution Solution Solution (Ideas to address opportunity) / \Experiment Experiment(Cheapest way to test)```### Rules1. **Outcomes** are business results you're trying to drive (from OKRs)2. **Opportunities** are customer needs, pain points, or desires (from discovery)3. **Solutions** are ideas for addressing opportunities (brainstormed)4. **Experiments** are the cheapest way to test if a solution works5. **Always compare 3+ solutions** per opportunity before picking one---## Application### Step 1: Define the Outcome```markdown**Desired Outcome:** [From OKR — e.g., "Increase 7-day activation from 28% to 55%"]**Why this outcome:** [Connection to business strategy]```### Step 2: Map Opportunities```markdown**Opportunities (customer needs that, if addressed, would drive the outcome):**1. [Opportunity 1 — e.g., "Users don't understand core value during trial"] - Evidence: [Interview quotes, data] - Size: [# users affected]2. [Opportunity 2 — e.g., "Data connection step is too technical"] - Evidence: [Drop-off data] - Size: [# users affected]3. [Opportunity 3]```### Step 3: Generate Solutions (3+ per opportunity)```markdown**Solutions for Opportunity 1:**| Solution | Effort | Confidence | Notes ||----------|--------|-----------|-------|| [Solution A] | [S/M/L] | [H/M/L] | [Rationale] || [Solution B] | [S/M/L] | [H/M/L] | [Rationale] || [Solution C] | [S/M/L] | [H/M/L] | [Rationale] |```### Step 4: Design Experiments```markdown**Experiment for [chosen solution]:**- **Type:** [Prototype test / Fake door / A/B test / Concierge]- **What we'll learn:** [Specific question]- **Success criteria:** [Metric + threshold]- **Duration:** [Days/weeks]- **Cost:** [Effort to run]```---## Quality Rubric| Dimension | 0 | 1 | 2 ||-----------|---|---|---|| **Outcome** | Not defined | Vague goal | Measurable from OKR || **Opportunities** | Assumed | Listed from intuition | Evidence-backed from research || **Solution Diversity** | 1 solution (pet idea) | 2 solutions | 3+ solutions compared || **Experiments** | None (just build it) | High-cost experiment | Cheapest test possible || **Evidence** | All assumption | Some data | Research-backed at each level |---## References### Related Skills- `skills/strategy/okr-framework/SKILL.md` — Outcome comes from OKRs- `skills/discovery/problem-statement/SKILL.md` — Opportunities from validated problems- `skills/growth/ab-test-design/SKILL.md` — Experiment design### External Frameworks- Teresa Torres, *Continuous Discovery Habits* (2021)---**Skill type:** Component**Domain:** Specification & Design

Frequently asked questions

Opportunity Solution Tree