Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to opportunities, solutions, and experiments. Based on Teresa Torres' Continuous Discovery Habits. Use when structuring discovery work, mapping opportunities to solutions, or deciding what to build next.
64
75%
Does it follow best practices?
Impact
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Passed
No known issues
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npx tessl skill review --optimize ./pm-product-discovery/skills/opportunity-solution-tree/SKILL.mdQuality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong description that clearly identifies a specific framework (Opportunity Solution Tree), names concrete actions (mapping outcomes to opportunities, solutions, and experiments), and provides explicit trigger guidance. The attribution to Teresa Torres' Continuous Discovery Habits further sharpens distinctiveness and helps Claude match this skill to relevant user requests.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Build an Opportunity Solution Tree', 'map a desired outcome to opportunities, solutions, and experiments', and 'structuring discovery work'. It also names the specific framework (Teresa Torres' Continuous Discovery Habits). | 3 / 3 |
Completeness | Clearly answers both 'what' (build an OST to structure product discovery, map outcomes to opportunities/solutions/experiments) and 'when' (explicit 'Use when structuring discovery work, mapping opportunities to solutions, or deciding what to build next'). | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'Opportunity Solution Tree', 'OST', 'product discovery', 'opportunities', 'solutions', 'experiments', 'what to build next', 'discovery work'. These cover both the formal framework name and natural language variations. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive — references a specific framework (Opportunity Solution Tree / Teresa Torres) and a clear niche (product discovery structuring). Unlikely to conflict with generic product management or roadmapping skills due to the specific methodology named. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides a solid conceptual framework for building an Opportunity Solution Tree but leans too heavily on explaining the methodology rather than showing Claude exactly what to produce. It would benefit significantly from a concrete example of a completed OST output (even a small one) and from trimming the domain context that explains well-known product discovery concepts. The workflow is reasonable but lacks the validation steps and concrete output templates that would make it truly actionable.
Suggestions
Add a concrete example of a completed mini-OST in markdown format showing the expected output structure (outcome → opportunities → solutions → experiments) so Claude knows exactly what to produce.
Trim the Domain Context section significantly — remove explanations of what opportunities and experiments are conceptually, and focus on the specific formatting/scoring rules Claude needs to follow.
Add an example experiment specification with filled-in hypothesis, method, metric, and success threshold fields to make step 5 actionable rather than abstract.
Include a validation checkpoint after step 2 (e.g., 'Confirm opportunities are framed from customer perspective and not disguised features') and after step 5 (e.g., 'Verify each experiment has all four fields specified').
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The domain context section explains concepts like what an OST is, its structure, and key principles at length. While some of this is useful framing, much of it (e.g., explaining what opportunities vs features are, quoting principles Claude could infer) is verbose. The quotes and attributions add tokens without adding actionability. | 2 / 3 |
Actionability | The process steps provide a reasonable sequence but remain at a high level of abstraction — there are no concrete examples of a completed OST, no template markdown output, no sample experiment format. The Opportunity Score formula is a nice concrete detail, but overall the skill describes what to do rather than showing executable examples of the output. | 2 / 3 |
Workflow Clarity | The 6-step process is clearly sequenced and logical, but lacks validation checkpoints or feedback loops. Step 4 mentions 'most promising solutions' without criteria for selection, and there's no explicit guidance on what to do when experiments fail beyond a brief mention in the principles section. For a multi-step discovery process, explicit checkpoints would strengthen this. | 2 / 3 |
Progressive Disclosure | The Further Reading section provides external references, but the skill itself is monolithic — the lengthy domain context, principles, and process are all inline. The domain context section could be separated or significantly trimmed. The external links are to web articles rather than companion skill files, limiting their utility in a skill context. | 2 / 3 |
Total | 8 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
020ee82
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