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Creates an opportunity solution tree connecting a desired outcome to customer opportunities and candidate solutions, preventing solution-first jumps in continuous discovery.
Passed 22 of 23 test cases with the skill, and 17 of 23 without it.
and 2 more in the full report
5 fixed17 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
We want to increase our e-commerce checkout completion rate from 62% to 75%. Our team has gathered various customer feedback quotes, drop-off analytics, and support complaints, but people keep jumping straight to feature ideas. Please build an Opportunity Solution Tree for this goal that maps our target metric to user pain points with evidence, branches out into potential solutions, and defines assumption experiments for our priority path.
| Checked | Without skill | With skill |
|---|---|---|
| Includes a dedicated Learning Log section tracking hypotheses, outcomes, or key takeaways. | Missed | Passed |
| Frames opportunity nodes as customer pain points or needs rather than pre-determined feature solutions. | Passed | Passed |
| Attaches qualitative or quantitative evidence to each identified opportunity branch. | Passed | Passed |
The instructions your model reads when the skill loads.
An Opportunity Solution Tree (OST) is a visual framework for product discovery that connects business outcomes to customer opportunities and potential solutions. Developed by Teresa Torres, it prevents the common trap of jumping straight to solutions by ensuring every feature idea traces back to a customer need and measurable outcome.
define-prioritization-framework; the tree structures discovery, not a ranking exercisedefine-problem-statementdefine-hypothesis, then measure-experiment-designfoundation-okr-writer; a tree without an agreed outcome decorates opinionsWhen asked to create an opportunity solution tree, follow these steps:
Define the Desired Outcome Start at the top with a clear, measurable business or product outcome. This should be something you can influence through product changes. Express it quantitatively when possible (e.g., "Increase 30-day retention from 40% to 55%").
Identify Opportunity Areas Branch out to 3-5 opportunity areas.places where customer needs or pain points could be addressed. Opportunities are not solutions; they're customer problems, needs, or desires. Phrase them from the customer's perspective.
Add Supporting Evidence For each opportunity, note the evidence that supports it: user research quotes, behavioral data, support tickets, or market trends. Strong opportunities have multiple evidence sources.
Brainstorm Solutions For each opportunity, generate 2-4 potential solutions. Don't self-censor at this stage. Solutions can range from quick experiments to major features. Keep them specific enough to evaluate.
Define Assumption Tests For each promising solution, identify the riskiest assumption and design a lightweight experiment to test it. Good tests validate whether the solution will actually address the opportunity.
test cases passed, vs 17 / 23 without
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