opportunity-mapping

opportunity-mapping is a skill for Claude Code from assimovt/productskills. It costs 47 tokens per session (749 once invoked), scanned A, original, MIT.

A product-planning method that links a business goal to customer needs, possible solutions, and experiments. It uses Opportunity Solution Trees, a diagram for exploring what to build and why.

In plain words
What is it for?
Use it to identify product opportunities, find gaps, explore solution ideas, and connect business outcomes with customer research and tests.
Why use it?
It helps avoid building features before confirming the customer problem, or pursuing customer problems that do not support a business goal.

Skill for Claude Code

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

Part of the product-skills plugin — 16 skills shipped together

Good fit Use it to identify product opportunities, find gaps, explore solution ideas, and connect business outcomes with customer research and tests.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/assimovt/productskills/opportunity-mapping
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 assimovt/productskills --skill opportunity-mapping
Clone the repo
git clone --depth 1 https://github.com/assimovt/productskills

Made for: Claude Code.

Or install product-skills, the plugin that ships this one along with the rest of its 16 skills.

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 opportunity-mapping

README.md
[![agentmods](https://agentmods.dev/badge/skills/assimovt/productskills/opportunity-mapping/github.svg)](https://agentmods.dev/skills/assimovt/productskills/opportunity-mapping)
Your own site
<a href="https://agentmods.dev/skills/assimovt/productskills/opportunity-mapping"><img src="https://agentmods.dev/badge/skills/assimovt/productskills/opportunity-mapping/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 opportunity-mapping

Your own site · 80×15
<a href="https://agentmods.dev/skills/assimovt/productskills/opportunity-mapping"><img src="https://agentmods.dev/badge/skills/assimovt/productskills/opportunity-mapping.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 749 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.
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 $0.00047 $0.00749
Opus 5 $0.00023 $0.00375
Sonnet 5 $0.00009 $0.00150
Haiku 4.5 $0.00005 $0.00075

Measured 11d ago against content hash 3162741dffb3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

opportunity-mapping 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 11d 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.

skills/opportunity-mapping/SKILL.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Map opportunities by connecting business outcomes to customer needs to testable solutions. Teresa Torres' Opportunity Solution Trees (OSTs) prevent the two biggest PM mistakes: building solutions without clear problems, and chasing problems disconnected from business goals.

Opportunity Solution Tree Structure

Build the tree top-down, but fill it bottom-up with evidence:

Desired Outcome (business metric you're trying to move)
  |
  +-- Opportunity 1 (customer need/pain/desire)
  |     +-- Solution A
  |     |     +-- Experiment 1
  |     |     +-- Experiment 2
  |     +-- Solution B
  |           +-- Experiment 3
  |
  +-- Opportunity 2
        +-- Solution C
        +-- Solution D
              +-- Experiment 4

Level 1: Desired Outcome

One measurable business outcome. Not a feature, not a project — a metric.

  • "Increase 7-day activation rate from 23% to 40%"
  • NOT: "Improve onboarding" (not measurable)

Level 2: Opportunities

Customer needs, pain points, or desires that, if addressed, would move the outcome. These come from research — interviews, data, support tickets — not brainstorming.

Rules for good opportunities:

  • Framed as customer needs, not product features
  • "New users don't understand what to do first" (opportunity)
  • NOT "Add an onboarding wizard" (solution masquerading as opportunity)
  • Each opportunity is independent — addressing one doesn't depend on another

Level 3: Solutions

Multiple possible solutions for each opportunity. Generate at least 3 before evaluating. The goal is to explore the solution space, not commit to the first idea.

Level 4: Experiments

Small, fast tests to validate whether a solution addresses the opportunity. Experiments should answer: "Does this solution actually solve this opportunity?"

Building the Tree

  1. Start with the outcome. Align with your team or stakeholders on exactly one outcome to focus on.
  2. Map opportunities from research. Review interview notes, support tickets, analytics. Cluster evidence into distinct opportunities. Each opportunity needs evidence from 3+ sources.
  3. Generate solutions per opportunity. Brainstorm at least 3 solutions per opportunity. Include wild ideas — they often reveal assumptions.
  4. Design experiments per solution. What's the smallest test? Prototype, concierge, Wizard of Oz, fake door, A/B test.
  5. Prioritize which branch to explore. You can't test everything. Pick the opportunity with strongest evidence and the solution with lowest experiment cost.

Read the full file on GitHub · 72 lines

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. 11d ago First seen · 72 lines · 47 tokens per session scan A 3162741dffb3

Subscribe to this mod's changes

opportunity-mapping is a skill published in the GitHub repository assimovt/productskills (68 stars, last pushed 6mo ago), licensed MIT. It adds 47 tokens to every session and 749 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 2026-08-30.

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