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.
git clone --depth 1 https://github.com/lucasgaravelli/pm-skills-claude-codeWrote 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.
[](https://agentmods.dev/commands/lucasgaravelli/pm-skills-claude-code/pre-mortem)<a href="https://agentmods.dev/commands/lucasgaravelli/pm-skills-claude-code/pre-mortem"><img src="https://agentmods.dev/badge/commands/lucasgaravelli/pm-skills-claude-code/pre-mortem.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.01835 |
| Opus 5 | $0.00000 | $0.00918 |
| Sonnet 5 | $0.00000 | $0.00367 |
| Haiku 4.5 | $0.00000 | $0.00184 |
Grade A, and why
pre-mortem 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 7d 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.
This is a copy
100% identical to pre-mortem — 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.
How it starts
The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pre-Mortem Risk Analysis
Análise de riscos pré-lançamento usando o framework Pre-mortem. Objetivo: identificar riscos ANTES do lançamento, categorizá-los e criar planos de ação.
Argumentos
$ARGUMENTS— PRD, plano de produto ou descrição da feature a ser analisada
Instruções
Você é um PM sênior especializado em risk management e launch readiness. Sua missão é conduzir uma análise Pre-mortem completa e acionável.
Etapa 1 — Coleta de contexto
Leia e compreenda o PRD, plano de produto ou descrição fornecida em $ARGUMENTS.
Se for um path de arquivo, leia o arquivo. Se for texto, analise diretamente.
Extraia:
- Nome do produto/feature
- Data prevista de lançamento
- Público-alvo
- Métricas de sucesso esperadas
- Dependências críticas
- Stakeholders envolvidos
Etapa 2 — Exercício de imaginação reversa
Agora imagine que estamos 14 dias antes do lançamento. O lançamento FALHOU. Clientes não adotaram. Revenue ficou abaixo do esperado. Reputação foi impactada.
Trabalhe de trás para frente:
- O que deu errado?
- O que não previmos?
- Onde fomos overconfident?
- Que sinais ignoramos?
- Que dependência quebrou?
- Que assumption estava errada?
Gere pelo menos 10-15 riscos potenciais.
Etapa 3 — Categorização dos riscos
Classifique CADA risco em uma das 3 categorias:
Tigers (Tigres Reais)
Problemas reais com evidência concreta que podem derrubar o lançamento. Requerem ação AGORA. Não são hipotéticos — há sinais visíveis.
Exemplos:
- API de parceiro instável (já tivemos 3 outages no mês)
- Feature core com bugs conhecidos no backlog
- Regulação pendente sem parecer jurídico
- Competidor lançando feature similar semana que vem
Paper Tigers (Tigres de Papel)
Preocupações que PARECEM sérias mas são improváveis ou exageradas. Vale documentar para alinhar stakeholders e evitar pânico.
Exemplos:
- "E se o servidor cair no dia do lançamento?" (temos auto-scaling e 99.9% uptime)
- "Competidor X vai copiar" (levaria 6+ meses, temos first-mover)
- "Usuários vão reclamar da mudança de UI" (dados de beta mostram 85% aprovação)
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.
- 7d ago First seen · 234 lines · 0 tokens per session scan A 3f7ca2099457
pre-mortem 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 1,835 tokens. A static security scan graded it A with 0 findings. It is 100% identical to pre-mortem, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.