Install
$ agentstack add skill-yuusakuri-agent-skills-define-opportunity-tree ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Opportunity Solution Tree
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.
When to Use
- During continuous product discovery to organize learning
- When prioritizing what opportunities to pursue
- To communicate product strategy to stakeholders
- When you have too many feature ideas and need structure
- After user research to connect insights to action
- When aligning team on what outcomes matter most
When NOT to Use
- You need to score and rank a flat list of known candidates -> use
prioritization-frameworks; the tree structures discovery, not a ranking exercise - You have one specific problem to frame for a team -> use
define-problem-statement - You are ready to test a single assumption -> use
define-hypothesis, thenmeasure-experiment-design - The outcome you want to drive is not yet agreed -> set it first with
brainstorm-okrs; a tree without an agreed outcome decorates opinions
Instructions
When 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.
- Prioritize the Tree
Not all branches are equal. Mark which opportunity and solution you'll pursue first based on potential impact, confidence, and effort. The tree is a living document.you'll iterate as you learn.
- Visualize the Structure
Create a tree diagram showing the hierarchy: outcome at top, opportunities below, solutions beneath each opportunity, and experiments at the leaves.
Output Format
Use the template in references/TEMPLATE.md to structure the output. A complete tree fills every template section: Desired Outcome; Visual Tree; Opportunity Branches; Prioritization; Experiments Backlog; Learning Log; and Next Steps.
Quality Checklist
Before finalizing, verify:
- [ ] Outcome is measurable and within product team's influence
- [ ] Opportunities are customer-centric (needs/problems, not features)
- [ ] Each opportunity has supporting evidence documented
- [ ] Multiple solutions exist per opportunity (not jumping to one)
- [ ] Assumptions are explicit and experiments designed
- [ ] Prioritization is clear (which branch to explore first)
Examples
See references/EXAMPLE.md for a completed example.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: yuusakuri
- Source: yuusakuri/agent-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.