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.
npx agentmods add commands/matheusbrramos/productflow/pf-specgit clone --depth 1 https://github.com/matheusbrramos/ProductFlowWrote 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/matheusbrramos/productflow/pf-spec)<a href="https://agentmods.dev/commands/matheusbrramos/productflow/pf-spec"><img src="https://agentmods.dev/badge/commands/matheusbrramos/productflow/pf-spec.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 | $0.00015 | $0.00956 |
| Opus 5 | $0.00008 | $0.00478 |
| Sonnet 5 | $0.00003 | $0.00191 |
| Haiku 4.5 | $0.00002 | $0.00096 |
Grade A, and why
pf-spec 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/pf-spec - Criar Software Design Document
Cria um SDD (Software Design Document) completo a partir de um PRD aprovado, definindo a arquitetura tecnica e decisoes de implementacao.
Entrada
$ARGUMENTS
Se nenhum argumento for fornecido, perguntar qual feature ou PRD usar como base.
Pre-requisitos
- PRD aprovado deve existir em
docs/prd/ .context/empresa.mddeve existir
Se PRD nao existir, orientar a rodar /prd primeiro.
O que fazer
-
Carregar contexto
- Ler PRD relacionado
- Verificar user stories existentes
- Entender restricoes tecnicas
-
Criar SDD completo com todas as secoes:
- Visao Geral (objetivo, escopo, referencias)
- Contexto e Restricoes (sistema atual, restricoes tecnicas, premissas)
- Arquitetura Proposta (diagrama, componentes, fluxo de dados)
- Design Detalhado (por componente: responsabilidades, interface, modelo de dados)
- Integracao (dependencias internas/externas, contratos de API)
- Seguranca (autenticacao, autorizacao, criptografia, auditoria)
- Performance e Escalabilidade (requisitos, estrategia, caching)
- Observabilidade (metricas, logs, alertas)
- Testes (estrategia, dados de teste)
- Plano de Rollout (fases, feature flags, rollback)
- Riscos Tecnicos (probabilidade, impacto, mitigacao)
- Decisoes de Design (ADRs)
-
Garantir rastreabilidade
- Linkar requisitos do PRD
- Referenciar user stories
- Conectar com analise competitiva
REGRAS CRITICAS
- SDD define O COMO tecnico (arquitetura, tecnologias, APIs)
- Deve ser consistente com os requisitos do PRD
- Marcar [NEEDS TECH REVIEW] para decisoes que precisam validacao
- Nao alterar requisitos definidos no PRD
Output
Criar arquivo: docs/sdd/{feature}.md
Usar template em docs/templates/sdd-template.md
Estrutura do Output
# SDD: [Nome da Feature]
**Versao:** 1.0
**Data:** YYYY-MM-DD
**Status:** Draft | Em Revisao | Aprovado
**PRD Relacionado:** docs/prd/{feature}.md
**Autor:** [nome]
## 1. Visao Geral
### Objetivo
### Escopo
### Referencias
## 2. Contexto e Restricoes
### Contexto do Sistema
### Restricoes Tecnicas
### Premissas Tecnicas
## 3. Arquitetura Proposta
### Diagrama de Alto Nivel
### Componentes Principais
### Fluxo de Dados
## 4. Design Detalhado
### 4.1 [Componente 1]
#### Responsabilidades
#### Interface
#### Modelo de Dados
#### Comportamento
## 5. Integracao
### Dependencias Internas
### Dependencias Externas
### Contratos de API
## 6. Seguranca
### Autenticacao
### Autorizacao
### Criptografia
### Auditoria
## 7. Performance e Escalabilidade
### Requisitos de Performance
### Estrategia de Escalabilidade
### Caching
## 8. Observabilidade
### Metricas
### Logs
### Alertas
## 9. Testes
### Estrategia de Testes
### Dados de Teste
## 10. Plano de Rollout
### Fases
### Feature Flags
### Rollback
## 11. Riscos Tecnicos
## 12. Decisoes de Design (ADRs)
## Historico de Versoes
## Aprovacoes
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.
- 5d ago First seen · 147 lines · 15 tokens per session scan A d1520d0ef454
pf-spec is a command published in the GitHub repository matheusbrramos/ProductFlow (2 stars, last pushed 5mo ago), licensed MIT. It adds 15 tokens to every session and 956 once invoked, about $0.0001 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 2026-08-31.
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.