A visual framework for structuring continuous product discovery. Connects a desired outcome to customer opportunities, possible solutions, and experiments to validate them.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionopportunity-solution-treeExecute the skills CLI command in your project's root directory to begin installation:
Fetches opportunity-solution-tree from phuryn/pm-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate opportunity-solution-tree. Access via /opportunity-solution-tree in your agent's command palette.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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A visual framework for structuring continuous product discovery. Connects a desired outcome to customer opportunities, possible solutions, and experiments to validate them.
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):
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.
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.
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."
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:
You are helping a product team build an Opportunity Solution Tree for $ARGUMENTS.
Define the desired outcome — Confirm or help articulate a single, measurable outcome at the top of the tree.
Map opportunities — From provided research, identify 3-7 customer opportunities (needs/pains). Group related opportunities. Frame each from the customer's perspective.
Prioritize opportunities — Use Opportunity Score or qualitative assessment to rank. Focus on the top 2-3.
Generate solutions — For each prioritized opportunity, brainstorm 3+ solutions from PM, Designer, and Engineer perspectives.
Design experiments — For the most promising solutions, suggest 1-2 fast experiments. Specify: hypothesis, method, metric, success threshold.
Visualize the tree — Present the full OST in a clear hierarchical format.
Think step by step. Save as markdown if substantial.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
Solid pick for teams standardizing on skills: opportunity-solution-tree is focused, and the summary matches what you get after install.
opportunity-solution-tree has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added opportunity-solution-tree from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
opportunity-solution-tree fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in opportunity-solution-tree — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
opportunity-solution-tree fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added opportunity-solution-tree from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
opportunity-solution-tree reduced setup friction for our internal harness; good balance of opinion and flexibility.
opportunity-solution-tree has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for opportunity-solution-tree matched our evaluation — installs cleanly and behaves as described in the markdown.
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