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opportunity-solution-tree

Skill34 starsChanged 8 months agoMITView on GitHub

Structure product discovery with Teresa Torres' Opportunity Solution Tree - outcome, opportunities, solutions, experiments

We split this skill into the rules it gives an agent

4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 21 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    One outcome at a time: Don't try to solve everything.

    line 34
  2. Distinctive:

    Compare and contrast: Always generate at least 3 solutions per opportunity before choosing.

    line 36
  3. Distinctive:

    Continuous, not periodic: Update the tree weekly as you learn from interviews, analytics, and experiments.

    line 38
  4. Distinctive:

    Prioritize opportunities: - Use Opportunity Score or qualitative assessment to rank.

    line 55

“Common” is measured: kept by at least 6 in 10 of the 21 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md
<!-- This skill is ported from phuryn/pm-skills under the MIT License. Copyright (c) 2026 Pawel Huryn. Upstream: https://github.com/phuryn/pm-skills/blob/main/pm-product-discovery/skills/opportunity-solution-tree/SKILL.md See ./ATTRIBUTION.md for the full license text. -->

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

Download now (ZIP)

  • Other versions22 projects use a version of this.

    Word for word · 0

    None found.

    Wrote their own version · 15

    1. deanpeters/Product-Manager-Skills★ 7.7ksame name
    2. itseffi/agentic-os★ 114same name
    3. avelikiy/great_cto★ 113same name
    4. drvoss/everything-copilot-cli★ 49same name
    5. DIAL-Studio/pm-agent-harness-kit★ 12same name
    6. The-Utopia-Studio/skills★ 6same name
    7. agrivisionai/claude-skills★ 1same name
    8. luisabwk/kraken★ 1same name
    9. nandanosql/all_in_one_pm_skills★ 1same name
    10. varunk130/claude-code-skills★ 1same name

    5 more not listed

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

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