prioritize

prioritize is a command for Claude Code from lucasgaravelli/pm-skills-claude-code. It costs 0 tokens per session (3,309 once invoked), scanned A, a copy of prioritize, MIT.

A backlog-prioritization workflow that scores ideas by reach, impact, confidence, and effort. A backlog is the list of possible work a product team may do.

In plain words
What is it for?
Use it to rank features, account for business goals and technical dependencies, choose what to leave out, and suggest an execution order or sprint plan.
Why use it?
It helps teams decide what to do first when there are many ideas, limited time, or disagreements between stakeholders. It also records the trade-offs behind the ranking.

Command for Claude Code

Written for Claude Code: installed under .claude/.

Good fit Use it to rank features, account for business goals and technical dependencies, choose what to leave out, and suggest an execution order or sprint plan.

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

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

Your own site · 80×15
<a href="https://agentmods.dev/commands/lucasgaravelli/pm-skills-claude-code/prioritize"><img src="https://agentmods.dev/badge/commands/lucasgaravelli/pm-skills-claude-code/prioritize.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 3,309 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 $0.03309
Opus 5 $0.00000 $0.01655
Sonnet 5 $0.00000 $0.00662
Haiku 4.5 $0.00000 $0.00331

Measured 9d ago against content hash 5688afe811b6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

prioritize 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 9d 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 prioritize — 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/prioritize.md · 421 lines

How it starts

The opening of the file, as written. The whole thing — 421 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/prioritize

O que essa skill faz

Aplica RICE scoring (Reach, Impact, Confidence, Effort) + contexto de negócio para priorizar backlog.

Saída: Backlog priorizado com scores, trade-offs explícitos, e recomendação de sequência.


Quando usar

  • Tem 5+ features/ideias e não sabe por onde começar
  • Stakeholders discordam sobre prioridade
  • Precisa explicar por quê escolheu A antes de B

Input esperado

Mínimo:

  • Lista de features/ideias: Nomes e breves descrições
  • Contexto de negócio: Metas desse trimestre
  • Constraints: Team size, deadline

Opcional:

  • Dados de impacto (churn reduction, revenue, CAC)
  • Dependências técnicas
  • Recursos de discovery já feitos

Processo

  1. RICE scoring — Cada feature scores em 4 dimensões
  2. Ranking: Divide by effort, ordena por score
  3. Trade-offs: Se top 3 não cabem, qual deixa?
  4. Sequência: Ordem de execução considerando dependências
  5. Roadmap: Qual sprint faz qual feature?

Output

# Priorização: [Nome do Trimestre ou Iniciativa]

## Contexto

### Metas desse trimestre
- [Meta 1]
- [Meta 2]
- [Meta 3]

### Constraints
- Team: [X eng, Y design, Z PM]
- Timeline: [Semanas disponíveis]
- Dependências: [O que bloqueia]

---

## RICE Scoring

### Explicação de cada dimensão

**Reach** (alcance de usuários)
- 100+ = 3 pontos
- 10-100 = 2 pontos
- 1-10 = 1 ponto

**Impact** (tamanho do efeito em cada usuário)
- Massivo (+50% métrica) = 3 pontos
- Grande (+10-50%) = 2 pontos
- Pequeno (+1-10%) = 1 ponto

**Confidence** (quão certo você está dos números)
- Muito certo (dados/descoberta) = 100%
- Confiante (validação informal) = 80%
- Suposição (hipótese não testada) = 50%

**Effort** (semanas de trabalho)
- RICE = (Reach × Impact × Confidence) / Effort
- Maior score = maior prioridade

---

## Features Priorizadas

| # | Feature | Reach | Impact | Conf | Effort | Score | Razão |
|---|---------|-------|--------|------|--------|-------|-------|
| 1 | [Feature A] | 3 | 3 | 100% | 2 | **4.5** | Alinha com meta 1, dados sólidos |
| 2 | [Feature B] | 2 | 2 | 80% | 3 | **1.07** | Nice-to-have, menos urgente |
| 3 | [Feature C] | 3 | 1 | 50% | 5 | **0.3** | Risky, sem validação ainda |

---

## Top 3 Recomendados

### 1. [Feature A] — Score 4.5 ⭐ Recomendado

**Caso de negócio**
- Reach: 200+ usuários (30% da base)
- Impact: +25% engagement (de 60% para 75%)
- Esforço: 2 semanas
- Alinha com: Meta 1 (Aumentar engagement)

**Detalhe**
- Já temos descoberta completa
- Risk baixo (feature similar existe no competitor)
- Quick win 1º

**Se fizer agora**
- Go-live: Semana 2
- Impacto esperado: +X MRR em 30 dias

---

### 2. [Feature B] — Score 1.07 ⭐ Considerar se tempo sobra

**Caso de negócio**
- Reach: 50 usuários (7% da base)
- Impact: +15% NPS (de 35 para 50)
- Esforço: 3 semanas
- Alinha com: Meta 2 (Customer satisfaction)

**Detalhe**
- Valor alto para essas 50 users mas impacto baixo no todo
- Confiança: 80% (validação com 5 clientes)
- Medium risk (requer integração externa)

**Se fizer depois**
- Seria prioridade para Q2
- Mantém cliente quality alta

---

### 3. [Feature C] — Score 0.3 ❌ Defer para Q2

**Caso de negócio**
- Reach: 150+ usuários
- Impact: +5% conversão (de 10% para 15%)
- Esforço: 5 semanas
- Alinha com: Meta 3 (Growth)

**Detalhe**
- HUGE incerteza (hipótese não testada)
- Effort alto = risco
- Recomendação: Validar com experimento ANTES de PRD

**Se não fizer agora**
- Não afeta trimestre
- Ganho tempo para validar melhor no Q2

---

## Trade-offs Explícitos

### Cenário A: Time pode fazer 2 features em paralelo

Semana 1-2: Feature A (1ª eng + design) Semana 1-3: Feature B (2ª eng) Semana 4: Buffer/polish


✅ Vantagem: Máximo impacto, ambas saem no mês
❌ Desvantagem: Team estressado, possível delay

### Cenário B: Time faz 1 feature por vez

Semana 1-2: Feature A → go-live Semana 3-5: Feature B → go-live Semana 6: Buffer


✅ Vantagem: Menos stress, mais qualidade, time pode responder bugs
❌ Desvantagem: Feature B sai mais tarde, possível pierde market window

### Recomendação
**Scenario B** — Feature A é quick win, deixa time com morale boost. Feature B é lower priority assim.

---

## Roadmap recomendado

### Semana 1-2: Feature A (MVP)
- Lançamento: Final da semana 2
- Métrica target: 20% de users ativos
- Go/No-go: Se < 10% de users adoptam, voltar ao drawing board

### Semana 3-5: Feature B (se aprovado)
- Dependência: A saiu + feedback coletado
- Lançamento: Final da semana 5
- Métrica target: 50% de segment satisfaction

### Semana 6: Polish/buffer
- Bugs de A ou B
- Surpresas

---

## O que fazer com Feature C

**Não é "cancela", é "defer + validate"**

1. Semana 1: Desenhar experimento para testar hipótese de C
2. Week 2-3: Rodar experimento com 100 usuários
3. Week 4: Análise — se validado, goes para Q2 roadmap como P0

Dessa forma, Q2 começa com Feature C já validado, sem risco.

---

## Aprovação

- [ ] PM: Priorização alinhada com metas
- [ ] Eng Lead: Estimates realistas
- [ ] Executive: Trade-offs aceitáveis

**Decisão**: [Feature A] vai para próximo sprint
**Data**: ________
**Próxima review**: [2 semanas, ou quando nova ideia aparecer]

Read the full file on GitHub · 421 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. 9d ago First seen · 421 lines · 0 tokens per session scan A 5688afe811b6

Subscribe to this mod's changes

prioritize 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 3,309 tokens. A static security scan graded it A with 0 findings. It is 100% identical to prioritize, differing in 0 lines, and is treated as a copy.