Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add georgemarmelstein/superjurista-dev/plugin install superjurista-devWrote 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/georgemarmelstein/superjurista-dev/criar-team)<a href="https://agentmods.dev/commands/georgemarmelstein/superjurista-dev/criar-team"><img src="https://agentmods.dev/badge/commands/georgemarmelstein/superjurista-dev/criar-team.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 | $0.00029 | $0.02129 |
| Opus 5 | $0.00015 | $0.01064 |
| Sonnet 5 | $0.00006 | $0.00426 |
| Haiku 4.5 | $0.00003 | $0.00213 |
Grade B, and why
criar-team scanned grade B with 1 finding 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 8d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
grep -q "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS" ~/.claude/settings.json && echo "HABILITADO" || echo "DESABILITADO" How it starts
The opening of the file, as written. The whole thing — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Comando: Criar Agent Team
```bash
grep -q "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS" ~/.claude/settings.json && echo "HABILITADO" || echo "DESABILITADO"
```
Registrar resultado para informar opções disponíveis.
**Pergunta:** "Qual abordagem de Agent Team você quer usar?"
**Opções:**
Se feature HABILITADA:
1. **v2.10 Agent Teams (Debate Real)** - Teammates debatem via mensagens, desafiam uns aos outros
2. **v2.8 Subagents (Paralelo)** - Executam isolados, consolidador sintetiza depois
Se feature DESABILITADA:
1. **v2.8 Subagents (Paralelo)** - Única opção disponível
2. **Habilitar v2.10** - Configurar feature e reiniciar
Explicar diferenças:
```
┌─────────────────────────────────────────────────────────────┐
│ v2.8 SUBAGENTS │ v2.10 AGENT TEAMS │
├─────────────────────────┼───────────────────────────────────┤
│ Paralelo isolado │ Debate via mensagens │
│ Comunicação: arquivos │ Comunicação: mensagens diretas │
│ Sem debate │ Teammates desafiam uns aos outros │
│ Funciona hoje │ Requer feature experimental │
│ Menos tokens │ Mais tokens │
└─────────────────────────┴───────────────────────────────────┘
```
1. Ler SPEC:
```
Read: ${CLAUDE_PLUGIN_ROOT}/spec/referencias/team-pattern.md
```
2. Fazer perguntas de descoberta:
- Objetivo do team
- Quantos teammates (2-4)
- Agents existentes para reutilizar
- Agent downstream
- Orquestrador de integração
3. Propor arquitetura
4. Gerar código:
- Teammates (agents que escrevem em arquivos separados)
- Consolidador (lê arquivos, sintetiza)
- Orquestrador (dispara Tasks em paralelo)
1. Ler SPEC:
```
Read: ${CLAUDE_PLUGIN_ROOT}/spec/referencias/agent-teams-v210.md
```
2. Fazer perguntas de descoberta:
- Objetivo do team (o que querem resolver/criar)
- Quantos teammates (2-5)
- Perspectivas distintas de cada um
- Tipo de debate (científico, criativo, revisão)
- Documento de convergência
3. Gerar PROMPT para o Lead:
O output não é código, é um PROMPT otimizado para o usuário
usar em uma nova sessão do Claude Code:
```markdown
# Prompt para Agent Team: [nome]
## Pré-requisitos
- Feature habilitada: ✅
- Reiniciar Claude Code antes de usar
## Prompt para o Lead
```
Crie um agent team com [N] teammates para [objetivo].
CONTEXTO:
[contexto relevante]
TEAMMATES:
1. [NOME-1]: [papel]
- Avalia pelo critério: "[critério]"
- Foco em [área]
2. [NOME-2]: [papel]
- Avalia pelo critério: "[critério]"
- Foco em [área]
[...]
PROCESSO:
1. Cada teammate produz sua análise/proposta
2. Cada um LÊ os outputs dos outros e CRITICA
3. Debate: desafiem as propostas, apontem falhas
4. Convergência: o que sobrevive ao escrutínio?
5. Lead sintetiza a recomendação final
O objetivo é que o DEBATE entre perspectivas diferentes
produza um resultado mais robusto do que cada um sozinho.
```
## Como Usar
1. Abra nova sessão do Claude Code
2. Cole o prompt acima
3. Observe o debate acontecer
4. Interaja com teammates se necessário (Shift+Up/Down)
```
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.
- 8d ago First seen · 258 lines · 29 tokens per session scan B 6b9e341d5b6f
criar-team is a command published in the GitHub repository georgemarmelstein/superjurista-dev (21 stars, last pushed 1mo ago), licensed MIT. It adds 29 tokens to every session and 2,129 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.