define-opportunity-tree

define-opportunity-tree is a skill for Claude Code from product-on-purpose/pm-skills. It costs 75 tokens per session (897 once invoked), scanned A, original, Apache-2.0.

A visual map that links a desired outcome to customer problems or needs and then to possible solutions. It organizes product discovery so teams understand the need before choosing what to build.

In plain words
What is it for?
Use it after user research, when organizing many feature ideas, or when explaining product strategy. It helps teams decide which customer opportunities and solutions deserve further investigation.
Why use it?
It prevents a list of ideas from turning directly into a roadmap without evidence of customer value. It shows how proposed work connects to outcomes and user needs.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the pm-skills plugin — 69 skills, 11 commands, 6 agents, 2 hooks shipped together

Good fit Use it after user research, when organizing many feature ideas, or when explaining product strategy. It helps teams decide which customer opportunities and solutions deserve further investigation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/product-on-purpose/pm-skills/define-opportunity-tree
Install

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.

Any agent
npx skills add product-on-purpose/pm-skills --skill define-opportunity-tree
Clone the repo
git clone --depth 1 https://github.com/product-on-purpose/pm-skills

Made for: Claude Code.

Or install pm-skills, the plugin that ships this one along with the rest of its 69 skills, 11 commands, 6 agents, 2 hooks.

Wrote 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.

agentmods badge for define-opportunity-tree

README.md
[![agentmods](https://agentmods.dev/badge/skills/product-on-purpose/pm-skills/define-opportunity-tree/github.svg)](https://agentmods.dev/skills/product-on-purpose/pm-skills/define-opportunity-tree)
Your own site
<a href="https://agentmods.dev/skills/product-on-purpose/pm-skills/define-opportunity-tree"><img src="https://agentmods.dev/badge/skills/product-on-purpose/pm-skills/define-opportunity-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.

agentmods 80×15 button for define-opportunity-tree

Your own site · 80×15
<a href="https://agentmods.dev/skills/product-on-purpose/pm-skills/define-opportunity-tree"><img src="https://agentmods.dev/badge/skills/product-on-purpose/pm-skills/define-opportunity-tree.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 897 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 23 Apr 2026
  • Snyk pass 23 Apr 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00075 $0.00897
Opus 5 $0.00037 $0.00449
Sonnet 5 $0.00015 $0.00179
Haiku 4.5 $0.00007 $0.00090

Measured 12d ago against content hash ebe0be2c0f8a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

define-opportunity-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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/define-opportunity-tree/SKILL.md · 77 lines

How it starts

The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 define-prioritization-framework; 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, then measure-experiment-design
  • The outcome you want to drive is not yet agreed -> set it first with foundation-okr-writer; a tree without an agreed outcome decorates opinions

Instructions

When asked to create an opportunity solution tree, follow these steps:

  1. 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%").

  2. 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.

  3. 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.

Read the full file on GitHub · 77 lines

Files

What ships with it

4 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.

Changes

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.

  1. 12d ago First seen · 77 lines · 75 tokens per session scan A ebe0be2c0f8a

Subscribe to this mod's changes

define-opportunity-tree is a skill published in the GitHub repository product-on-purpose/pm-skills (658 stars, last pushed today), licensed Apache-2.0. It adds 75 tokens to every session and 897 once invoked, about $0.0004 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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