opportunity-tree

opportunity-tree is a command for Claude Code from lucasgaravelli/pm-skills-claude-code. It costs 0 tokens per session (4,296 once invoked), scanned A, a copy of opportunity-tree, MIT.

A product-discovery map that connects a target result to user problems, possible solutions, and tests.

In plain words
What is it for?
Use it to organise user research and analytics, compare opportunities, rank them, and design experiments.
Why use it?
It helps teams explore several ways to improve a result before committing to a feature. It also gives product, design, and engineering a shared basis for deciding what to investigate.

Command for Claude Code

Written for Claude Code: installed under .claude/.

Good fit Use it to organise user research and analytics, compare opportunities, rank them, and design experiments.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/lucasgaravelli/pm-skills-claude-code/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.

Clone the repo
git clone --depth 1 https://github.com/lucasgaravelli/pm-skills-claude-code

Made for: Claude Code.

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-tree

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

Your own site · 80×15
<a href="https://agentmods.dev/commands/lucasgaravelli/pm-skills-claude-code/opportunity-tree"><img src="https://agentmods.dev/badge/commands/lucasgaravelli/pm-skills-claude-code/opportunity-tree.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,296 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 100% copy Near-identical to another mod 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 $0.00000 $0.04296
Opus 5 $0.00000 $0.02148
Sonnet 5 $0.00000 $0.00859
Haiku 4.5 $0.00000 $0.00430

Measured 10d ago against content hash 90c62f221f16, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

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 10d 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

This is a copy

100% identical to opportunity-tree — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/commands/opportunity-tree.md · 341 lines

How it starts

The opening of the file, as written. The whole thing — 341 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/opportunity-tree

O que essa skill faz

Gera uma Opportunity Solution Tree (OST) completa seguindo o framework de Teresa Torres (Continuous Discovery Habits). Estrutura o pensamento de discovery em 4 níveis: Outcome → Opportunities → Solutions → Experiments.

Saída: Árvore de oportunidades com scores, soluções comparadas e experimentos desenhados — pronta para alinhar o Product Trio.


Quando usar

  • Tem um outcome claro mas não sabe por onde começar
  • Quer priorizar oportunidades com base em dados, não intuição
  • Precisa gerar múltiplas soluções antes de se comprometer com uma
  • Quer alinhar PM, Designer e Tech Lead sobre o que explorar primeiro
  • Está preso no modo "feature factory" e quer voltar para discovery

Input esperado

Mínimo:

  • Desired Outcome: Métrica específica que quer mover (ex: "Aumentar retenção de 7 dias de 30% para 50%")
  • Contexto do produto: O que é o produto, quem usa
  • Dados disponíveis: Que pesquisas, entrevistas ou analytics existem

Opcional:

  • Trechos de entrevistas com usuários
  • Dados de analytics (funil, retenção, comportamento)
  • Oportunidades já identificadas
  • Constraints (budget, timeline, capacidade do time)
  • Personas definidas

Processo

  1. Definir UM outcome — Escolher uma única métrica mensurável com baseline e target. Não tente resolver tudo ao mesmo tempo. Ex: "Aumentar 7-day retention de 30% para 50%." Se o input tiver múltiplos outcomes, pedir para priorizar.

  2. Identificar 4-6 oportunidades — Extrair de pesquisa com usuários (entrevistas, surveys, analytics). Cada oportunidade deve ser um problema ou necessidade do cliente, NUNCA uma feature. Usar framing centrado no usuário: "Eu luto para..." ou "Eu gostaria de poder...". Se não houver dados, marcar como hipótese.

  3. Scorer oportunidades — Para cada oportunidade, avaliar:

    • Importância (1-5): Quanto isso importa para o usuário?
    • Satisfação (1-5): Quão bem resolvido está hoje?
    • Score = Importância × (1 − Satisfação/5)
    • Priorizar as 2-3 com maior score.

Read the full file on GitHub · 341 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. 10d ago First seen · 341 lines · 0 tokens per session scan A 90c62f221f16

Subscribe to this mod's changes

opportunity-tree is a command published in the GitHub repository lucasgaravelli/pm-skills-claude-code (20 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,296 tokens. A static security scan graded it A with 0 findings. It is 100% identical to opportunity-tree, differing in 0 lines, and is treated as a copy.