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 uthumany/uthy-legacy-os --skill opportunity-solution-treegit clone --depth 1 https://github.com/uthumany/uthy-legacy-osWrote 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/uthumany/uthy-legacy-os/opportunity-solution-tree)<a href="https://agentmods.dev/skills/uthumany/uthy-legacy-os/opportunity-solution-tree"><img src="https://agentmods.dev/badge/skills/uthumany/uthy-legacy-os/opportunity-solution-tree/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/uthumany/uthy-legacy-os/opportunity-solution-tree"><img src="https://agentmods.dev/badge/skills/uthumany/uthy-legacy-os/opportunity-solution-tree.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 | $0.00037 | $0.01191 |
| Opus 5 | $0.00018 | $0.00596 |
| Sonnet 5 | $0.00007 | $0.00238 |
| Haiku 4.5 | $0.00004 | $0.00119 |
Grade A, and why
opportunity-solution-tree 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Opportunity-Solution Tree
Overview
The Opportunity-Solution Tree (OST), popularized by Teresa Torres in Continuous Discovery Habits, is a visual framework that maps a desired outcome → opportunities (user needs, pain points, desires) → solutions → assumptions. It prevents the common mistake of jumping straight from a problem to a solution without exploring alternatives.
When to Use
- Starting a new product initiative with an outcome in mind
- Multiple stakeholders want different solutions — need to align on the problem first
- You've done discovery interviews and need to organize findings
- You want to avoid building the first solution that comes to mind
- Don't use for: well-understood execution work, bug fixes, or compliance requirements
Instructions
1. Define the Desired Outcome
Start at the top: what outcome are we trying to achieve?
- A measurable business outcome (increase retention, reduce support tickets)
- Not a solution ("build a chatbot") — that goes lower in the tree
- Example: "Reduce time-to-value for new team workspace setup from 2 days to 2 hours"
2. Identify Opportunities
Opportunities are user needs, pain points, and desires — not solutions.
- Each opportunity answers: "What would help users achieve the desired outcome?"
- Source them from customer interviews, analytics, support tickets, and research
- Write as statements of user need: "I can't find the right template to start with"
- Don't prioritize yet — just list them
3. Explore Solutions (for each opportunity)
For each opportunity, brainstorm 3-5 potential solutions:
- Divergent thinking: No judgment. Capture all ideas, even crazy ones
- Include obvious solutions and creative alternatives
- Solutions are concrete: "Auto-detect workspace type from email domain" not "make setup easier"
4. Surface Assumptions
For each solution, identify the assumptions you're making:
- Desirability: Will users actually want this?
- Viability: Can we build this profitably?
- Feasibility: Can we build this technically?
- Usability: Will users be able to use it?
- Prioritize which assumptions to test first (riskiest → easiest to test)
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 · 121 lines · 37 tokens per session scan A e71b703dba28
opportunity-solution-tree is a skill published in the GitHub repository uthumany/uthy-legacy-os (5 stars, last pushed 3mo ago), licensed MIT. It adds 37 tokens to every session and 1,191 once invoked, about $0.0002 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 2026-08-31.
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