Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add wdavidturner/product-skills --skill opportunity-solution-treesgit clone --depth 1 https://github.com/wdavidturner/product-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wdavidturner/product-skills/opportunity-solution-trees)<a href="https://agentmods.dev/skills/wdavidturner/product-skills/opportunity-solution-trees"><img src="https://agentmods.dev/badge/skills/wdavidturner/product-skills/opportunity-solution-trees/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wdavidturner/product-skills/opportunity-solution-trees"><img src="https://agentmods.dev/badge/skills/wdavidturner/product-skills/opportunity-solution-trees.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00068 | $0.01072 |
| Opus 5 | $0.00034 | $0.00536 |
| Sonnet 5 | $0.00014 | $0.00214 |
| Haiku 4.5 | $0.00007 | $0.00107 |
Grade A, and why
opportunity-solution-trees scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Opportunity Solution Trees
What It Is
Use the Opportunity Solution Tree (OST) to connect a business outcome to the customer opportunities that drive it, then compare solutions and tests. The tree forces you to separate needs from ideas and keeps discovery tied to delivery.
When to Use It
- Structure discovery around customer opportunities
- Tie customer needs to measurable outcomes
- Compare multiple solutions for the same opportunity
- Keep continuous discovery aligned with the roadmap
- Create a shared view of priorities with stakeholders
When Not to Use It
- You are not doing customer research
- The solution is already decided
- The work is a commodity requirement with no real options
- You only need a quick one-off decision
Patterns
Detailed examples showing how to apply OST correctly. Each pattern shows a common mistake and the correct approach.
Critical (get these wrong and you've wasted your time)
| Pattern | What It Teaches |
|---|---|
| opportunities-are-solutions | "Add a search bar" is a solution -- the opportunity is what's hard about finding things |
| starting-with-solutions | Work backward from outcomes, not forward from feature ideas |
| skipping-outcome | Without a clear outcome, you can't evaluate which opportunities matter most |
| interviewing-for-facts | Collect stories, not preferences -- needs emerge from what happened |
| conference-room-opportunities | You can't hypothesize opportunities without customer research |
High Impact
| Pattern | What It Teaches |
|---|---|
| single-solution-thinking | Always compare at least 3 solutions for any opportunity |
| opportunities-too-big | "Make it easier to use" is not actionable -- decompose into specific moments |
| flat-tree-structure | Opportunities should nest hierarchically from broad to specific |
| missing-experience-map | Structure opportunities around the customer journey, not internal categories |
| output-not-outcome | "Launch feature X" is an output -- "Increase activation by 10%" is an outcome |
| solution-testing-whole-idea | Break solutions into assumptions and test the riskiest ones first |
What ships with it
16 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- patterns/_template.md 460 B
- patterns/conference-room-opportunities.md 2.0 KB
- patterns/flat-tree-structure.md 2.6 KB
- patterns/interviewing-for-facts.md 2.2 KB
- patterns/missing-experience-map.md 2.2 KB
- patterns/needs-not-heard.md 2.2 KB
- patterns/opportunities-are-solutions.md 1.7 KB
- patterns/opportunities-too-big.md 2.2 KB
- patterns/output-not-outcome.md 2.4 KB
- patterns/single-solution-thinking.md 2.0 KB
- patterns/skipping-outcome.md 1.7 KB
- patterns/solution-testing-whole-idea.md 2.3 KB
- patterns/starting-with-solutions.md 2.1 KB
- patterns/too-many-branches.md 2.3 KB
- patterns/tree-not-updated.md 2.1 KB
- references/ost-playbook.md 3.7 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 103 lines · 68 tokens per session scan A cb4f6b6c4dc8
opportunity-solution-trees is a skill published in the GitHub repository wdavidturner/product-skills (20 stars, last pushed 7mo ago), licensed MIT. It adds 68 tokens to every session and 1,072 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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