Opportunity Solution Tree
Structure continuous discovery with Teresa Torres’ Opportunity Solution Tree so you pick outcomes, opportunities, and experiments before committing to features.
Overview
Opportunity Solution Tree is a journey-wide agent skill that maps a desired outcome to customer opportunities, solutions, and validation experiments—usable whenever a solo builder needs to decide what to build next befor
Install
npx skills add https://github.com/phuryn/pm-skills --skill opportunity-solution-treeWhat is this skill?
- Four-level OST: Desired Outcome → Opportunities → Solutions → Experiments
- Opportunity prioritization via Opportunity Score: Importance × (1 − Satisfaction)
- Frames opportunities as customer problems, not feature lists
- Grounded in Teresa Torres’ Continuous Discovery Habits
- Connects discovery work to OKRs and a single clear outcome metric
- 4-level OST structure (Outcome, Opportunities, Solutions, Experiments)
- Opportunity Score formula: Importance × (1 − Satisfaction) with 0–1 normalization
Adoption & trust: 1k installs on skills.sh; 12.3k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
You keep jumping to features or agent-generated code without a shared map from business outcome to customer problems and cheap experiments.
Who is it for?
Builders doing continuous discovery with interviews or support signals and one north-star metric tied to OKRs or strategy.
Skip if: Throwaway hacks with no learning goal, or when the desired outcome and success metric are already fixed and only implementation tasks remain.
When should I use this skill?
Structuring discovery work, mapping opportunities to solutions, deciding what to build next, or applying Continuous Discovery Habits.
What do I get? / Deliverables
You produce a structured OST with prioritized opportunities and experiment ideas so the next build step targets validated problems, not opinion.
- Opportunity Solution Tree outline
- Prioritized opportunities with Opportunity Scores
- Experiment list tied to solution branches
Recommended Skills
Journey fit
Useful at every journey phase - explore requirements and options before committing to a direction.
Where it fits
Turn interview themes into opportunity branches under a single outcome before you prototype.
Choose which customer problems the MVP must solve and which solutions need a smoke test first.
Pick the next epic by highest-scoring opportunity instead of the loudest feature request.
When metrics slip, add new opportunity branches and experiments instead of reactive refactors.
Link retention or activation gaps to opportunities and run small experiments before big growth bets.
How it compares
Use for discovery structure and opportunity prioritization—not for writing implementation plans line-by-line (pair with a planning skill after the tree is approved).
Common Questions / FAQ
Who is opportunity-solution-tree for?
Solo and indie product builders who act as their own PM and need Teresa Torres-style discovery without a full product trio.
When should I use opportunity-solution-tree?
Use it in Idea while synthesizing research, in Validate when scoping the MVP, in Build when choosing the next PM slice, and in Operate when retention drops and you need new opportunities—not new random features.
Is opportunity-solution-tree safe to install?
It is procedural PM documentation; check the Security Audits panel on this page if the parent repo bundles unrelated automation.
SKILL.md
READMESKILL.md - Opportunity Solution Tree
## Opportunity Solution Tree (OST) A visual framework for structuring continuous product discovery. Connects a desired **outcome** to customer **opportunities**, possible **solutions**, and **experiments** to validate them. ### 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 the team is 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. These are problems worth solving — not features. Frame them from the customer's perspective: "I struggle to..." or "I wish I could..." Prioritize using Opportunity Score: **Importance × (1 − Satisfaction)** (Dan Olsen, *The Lean Product Playbook*). Normalize Importance and Satisfaction to 0–1. 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. "Best ideas often come from engineers." 4. **Experiments** (bottom) — Fast, cheap tests to validate whether a solution actually addresses the opportunity. Use assumption testing (Value, Usability, Viability, Feasibility risks). Prefer experiments with "skin-in-the-game" (Alberto Savoia) over opinion-based validation. **Key principles:** - **One outcome at a time.** Don't try to solve everything. Focus the tree on a single desired outcome. - **Opportunities, not features.** "Never allow customers to design solutions. Prioritize opportunities (problems), not features." - **Compare and contrast.** Always generate at least 3 solutions per opportunity before choosing. Avoid the "first idea" trap. - **Discovery is not linear.** Loop back if experiments fail. Kill solutions that don't validate. Explore new branches. - **Continuous, not periodic.** Update the tree weekly as you learn from interviews, analytics, and experiments. ### Instructions You are helping a product team build an Opportunity Solution Tree for **$ARGUMENTS**. ### 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 ### Process 1. **Define the desired outcome** — Confirm or help articulate a single, measurable outcome at the top of the tree. 2. **Map opportunities** — From provided research, identify 3-7 customer opportunities (needs/pains). Group related opportunities. Frame each from the customer's perspective. 3. **Prioritize opportunities** — Use Opportunity Score or qualitative assessment to rank. Focus on the top 2-3. 4. **Generate solutions** — For each prioritized opportunity, brainstorm 3+ solutions from PM, Designer, and Engineer perspectives. 5. **Design experiments** — For the most promising solutions, suggest 1-2 fast experiments. Specify: hypothesis, method, metric, success threshold. 6. **Visualize the tree** — Present the full OST in a clear hierarchical format. Think step by step. Save as markdown if substantial. --- ### Further Reading - [The Extended Opportunity Solution Tree](https://www.productcompass.pm/p/the-extended-opportunity-solution-tree) - [What Is Product Discovery? The Ultimate Guide Step-by-Step](https