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Henrique Sanches Leal"},"license":"MIT","homepage":"https://github.com/pedrohenriquesanchesleal4-debug/izanagi-ai#readme","keywords":["izanagi","izanagi-ai","ai","agents","prompt-engineering","skills","cli","llm","code-generation","autonomous-agents"],"repository":{"url":"git+https://github.com/pedrohenriquesanchesleal4-debug/izanagi-ai.git","type":"git"},"description":"Izanagi AI - Modular Skill-Oriented AI Prompt & Agent Framework for Autonomous Software Engineering","maintainers":[{"name":"pedrohsl1","email":"pedrohenriquesanchesleal4@gmail.com"}],"readme":"# Izanagi AI\r\n\r\n> **v3.24.7** · npm estável: **3.24.5**. Runtime de execução de trabalho orientado a agentes. **Executa sem API key e sem modelo local**: se você já tem o `claude` (Claude Code CLI) instalado e autenticado, `izanagi run` faz trabalho de verdade usando essa autenticação, por subprocesso.\r\n>\r\n> Arquitetura: **Commander** → contrato de tarefa → roteamento por papel (por TAREFA, não por run) → grafo → verificação por evidência → healing → replan → memória. O run **lê o projeto** antes de decidir e **entrega arquivo** no fim, os dois por nós de tool com permissão declarada. Todo teto declarado (tokens, custo, tempo, retries, agentes, tool calls, concorrência, allowlist de tool) **é aplicado e tem teste que mede o teto**; `Ctrl-C` cancela o run e o `resume` retoma do último batch gravado. 23 agentes especializados, incluindo um coordenador orchestration-only, catálogo de skills v2, CLI publicada no npm (`izanagi-ai`), SDK programático e **topologia poliglota** (Rust · Go · Python · TypeScript) ao lado do runtime legado.\r\n\r\n**Filosofia:** Arquitetura primeiro. Código depois. Qualidade medida. Evolução contínua. Zero \"cara de IA\".\r\n\r\n---\r\n\r\n## Instalação\r\n\r\nRequisito: Node.js ≥ 18.\r\n\r\n```bash\r\nnpm install -g izanagi-ai    # instalação global\r\nnpx izanagi <comando>        # ou execução direta sem instalar\r\nizanagi --version\r\n```\r\n\r\n> O pacote é publicado como `izanagi-ai`; bins: `izanagi` e `izanagi-ai`.\r\n\r\n---\r\n\r\n## Executar sem API key\r\n\r\nO Izanagi precisa de um **executor**: alguém que rode os nós do grafo. Existem três caminhos, e o primeiro não pede chave nenhuma.\r\n\r\n```bash\r\nizanagi doctor     # diz qual executor está disponível AGORA\r\n```\r\n\r\n| Caminho | O que exige | Como o runtime o chama |\r\n|---|---|---|\r\n| **CLI de agente** (recomendado) | um agente de codificação já instalado e autenticado: hoje o `claude` no PATH | provider `claude-cli`, por subprocesso em modo print. **Zero configuração**: detectado no PATH |\r\n| API key | `IZANAGI_ANTHROPIC_API_KEY`, `IZANAGI_OPENAI_API_KEY`, `IZANAGI_GOOGLE_API_KEY`, `IZANAGI_OPENROUTER_API_KEY` | HTTP direto no provider |\r\n| Modelo local | `IZANAGI_OLLAMA_ENABLED=1` ou `IZANAGI_LMSTUDIO_ENABLED=1` | endpoint OpenAI-compatible em localhost |\r\n\r\nSem nenhum dos três, o run continua funcionando em **modo headless**: planeja, roteia e verifica de verdade, mas SIMULA o conteúdo dos nós. É o comportamento antigo, e agora ele é o último recurso, não o default de quem nunca configurou nada.\r\n\r\n```bash\r\n# nada além do Claude Code instalado:\r\nizanagi run \"Escreva a função validarCPF em TypeScript\" --output out\r\n#   ✔ Execução real: claude-cli\r\n#     via CLI de agente já autenticado (sem API key)\r\n#     tools do executor: none (--agent-tools read liga leitura do repositório)\r\n```\r\n\r\n### Os agentes valem em TODO projeto (escopo pessoal)\r\n\r\nAgente e skill são descobertos **por projeto**: abrir a CLI em outro diretório não encontra nenhum dos 22 agentes nem a biblioteca de skills, e a conclusão natural de quem vê isso é que o framework não funciona. Instale no escopo pessoal uma vez:\r\n\r\n```bash\r\nizanagi export --cli claude --global   # ~/.claude/{agents,commands,skills}\r\n```\r\n\r\nNunca escreve `~/CLAUDE.md`: esse arquivo é a memória global de quem usa, e sobrescrevê-lo injetaria a descrição de um framework em todo repositório aberto. Agentes e skills são aditivos e ficam inertes até serem chamados.\r\n\r\n### O orquestrador escolhe o modelo de cada agente\r\n\r\nO Commander é **determinístico**: classificar, decidir o modo, gerar contratos e estimar custo não gasta um token. O gasto acontece só nos nós, e cada nó recebe o modelo do PAPEL dele, com o agente tendo voz:\r\n\r\n```\r\nizanagi run agent-architect --task \"desenhar um agente novo\"\r\n\r\nexecute      agent-architect  commander   claude-opus-5     <- o agente declara `opus` no JSON dele\r\nverify       qa               specialist  claude-sonnet-5   <- papel specialist: tier balanced\r\nevaluation   -                worker      claude-haiku-4-5  <- tarefa pequena: tier fast\r\n```\r\n\r\nPrecedência: `--model` / pin por papel (`IZANAGI_MODEL_SPECIALIST`, config `roles`) > tier declarado pelo agente > default do papel. O hint é um TIER, não um id: `opus` num catálogo sem premium cai para o melhor disponível, e o mesmo agente roda em Anthropic, OpenAI, modelo local ou CLI de agente sem mudar nada.\r\n\r\n### Política de tools do executor\r\n\r\nO subprocesso roda **sem nenhuma tool por padrão** (`--restricted --tools \"\"`): nada de shell, nada de escrita, nenhum settings do projeto carregado. É o mais barato, o mais determinístico e o mais seguro.\r\n\r\n```bash\r\nizanagi run \"...\"                          # tools: none  (default)\r\nizanagi run \"...\" --agent-tools read       # Read/Grep/Glob: o executor LÊ o repositório\r\nizanagi run \"...\" --agent-tools write      # + Write/Edit: altera arquivos (opt-in explícito)\r\n```\r\n\r\n`write` é o único valor que autoriza alteração de arquivo, e Bash nunca entra em nenhuma das políticas.\r\n\r\n### Custo, medido\r\n\r\nO CLI devolve o custo real de cada chamada (`total_cost_usd`), então neste executor o custo do run **é medido, não estimado** por tabela de preço. Números observados nesta máquina, num nó de specialist com chain de skills:\r\n\r\n| Política | Tokens do nó | Observação |\r\n|---|---|---|\r\n| `none` | ~20.000 no modo `direct`, ~30.000 num nó de specialist | inclui o system prompt do CLI, cobrado em toda chamada |\r\n| `read` | ~68.000 | várias voltas de tool e contexto do repositório multiplicam o consumo |\r\n\r\nPor isso `--budget` apertado estoura no primeiro nó, e por isso **você não precisa passar `--budget`**: quando o executor é o CLI de agente, o teto default do run sobe sozinho para o piso desta tabela. Piso recomendado: **65.000** por nó com `none`, **148.000** com `read` (a CLI avisa quando um `--budget` explícito fica abaixo disso).\r\n\r\nO piso não é a média medida: é o topo da faixa observada, com folga de variância, dividido pela menor fatia que a fase `execution` recebe do teto (0,6). O erro aqui não é simétrico. Teto folgado não gasta um token a mais, porque o gasto é o que o nó consome e quem limita dinheiro é `--max-cost`, cobrado sobre custo MEDIDO; teto curto aborta o run **depois** de todo o custo já ter sido pago. Medido: com um piso dimensionado pela média, um run orchestrated produziu cinco artefatos válidos (7,4KB + 13,7KB + 23,7KB) e terminou sem gravar arquivo nenhum.\r\n\r\nTeto não é gasto: num run orchestrated real o teto ficou em 260.000 e o consumo medido foi 147.140 (US$ 0,94). Para limitar dinheiro, use `--max-cost`.\r\n\r\nControles: `IZANAGI_AGENT_CLI_DISABLED=1` desliga o executor · `IZANAGI_AGENT_CLI_TIMEOUT_MS` ajusta o timeout (default 300.000) · `IZANAGI_AGENT_CLI_TOOLS=read|write` é o equivalente de `--agent-tools` por ambiente. Dentro de um test runner o executor fica desligado por padrão, para que `npm test` nunca gaste cota real (`IZANAGI_AGENT_CLI_IN_TESTS=1` libera).\r\n\r\n---\r\n\r\n## Pesquisa aplicada: design, agentes e segundo cérebro\r\n\r\nAs referências encontradas nos posts salvos foram separadas entre inspiração e evidência. O framework absorve apenas padrões verificáveis:\r\n\r\n- **Design:** Apple HIG e Playwright reforçam decisões centradas no usuário, contratos explícitos e teste do comportamento visível; isso alimenta `anti-ai-slop`, `design-directions`, `motion-design` e o QA visual.\r\n- **Processo:** Spec Kit confirma o valor de separar constituição, especificação, plano, tarefas, implementação e convergência. O Izanagi já faz isso por contratos, grafo, verificação e journal; a especificação deve ser um artefato de entrada, não um prompt descartável.\r\n- **Segurança:** Strix e o padrão “produzir → refutar → corrigir” inspiram uma etapa adversarial, mas qualquer ferramenta externa deve ser validada por fonte oficial antes de entrar no catálogo.\r\n- **Segundo cérebro:** **Markdown é a fonte canônica e Obsidian é uma interface humana opcional**. Use `raw/`, `wiki/`, `decisions/` e `output/`; não introduza banco vetorial até um benchmark provar ganho. O grafo visual ajuda navegação, não substitui `MemoryStore`, `DecisionJournal` ou `EvidenceRegistry`.\r\n\r\nFontes e classificação: [`references/instagram-ai-leads-2026.md`](references/instagram-ai-leads-2026.md).\r\n\r\n**Integridade das skills:** o build valida que toda `SKILL.md` v2 tem alias no\r\nresolver e que toda skill declarada por um agent resolve para um arquivo real.\r\nNo runtime, skills explícitas do nó são preservadas quando o ranking dinâmico\r\nadiciona contexto; cada tarefa recebe no máximo três skills ranqueadas. Em uma\r\nmedição local de `--prompt-only --compact`, uma landing page gerou cerca de\r\n13k tokens de prompt, antes do overhead do executor; use `--compact` para\r\ndiscovery e reserve `read`/`write` para nós que realmente precisam do projeto.\r\n\r\n## Quick Start\r\n\r\n```bash\r\n# 1. Inicializa um projeto com .agents/ e seleção interativa de packs de skills\r\nizanagi init my-project\r\n#    ou sem interação: izanagi init my-project --packs core,agents,coding,database\r\n\r\n# 2. Executa uma tarefa. O modo é decidido pelo Commander, não fixo.\r\n#    Sem API key: basta ter o Claude Code CLI instalado (izanagi doctor confirma).\r\nizanagi run \"Converta 10 dólares para reais\"                  # modo direct: 1 chamada, sem grafo\r\nizanagi run \"Criar uma landing page de um SaaS de analytics\"  # modo composto, com verificação\r\nizanagi run \"...\" --mode autonomous --max-cost 0.50           # teto de custo respeitado no plano\r\nizanagi run \"adicionar paginação em GET /users\" --output docs # lê o projeto e entrega o arquivo\r\nizanagi run \"...\" --acceptance \"o endpoint aceita ?page e ?limit\"  # o que o usuário pediu, cobrado\r\nizanagi run \"...\" --output src --verify-tests                # a métrica de teste vem do exit code do projeto\r\nizanagi run \"...\" --min-quality 0.3                          # a estratégia mais barata que atinge o piso\r\nizanagi run \"...\" --reuse-artifacts                          # segundo run da mesma pergunta não repaga a chamada\r\nizanagi run \"...\" --agent-tools read                         # o executor lê o repositório antes de responder\r\n\r\n# 3. Observabilidade, custo e auditoria\r\nizanagi trace            # spans, healing, graph, avaliação\r\nizanagi budget <run-id>  # para onde foi o orçamento: tokens por fase, custo, cache, degradação\r\nizanagi models           # qual modelo cada papel receberia agora, e por quanto\r\nizanagi explain <run-id> # por que o Izanagi decidiu o que decidiu\r\nizanagi doctor           # integridade da instalação (--deep inclui security scan das skills)\r\n```\r\n\r\n### Execução proporcional ao problema\r\n\r\nO Commander classifica o objetivo (complexidade 1 a 5 + domínios) e escolhe um dos quatro modos. Antes, toda tarefa virava um grafo de 3 a 9 nós, inclusive \"converta 10 dólares para reais\".\r\n\r\n| Modo | Quando | Forma |\r\n|---|---|---|\r\n| `direct` | tarefa trivial de um domínio | 1 chamada, sem grafo, sem crítica |\r\n| `assisted` | tarefa simples | 1 especialista + verificação determinística |\r\n| `orchestrated` | problema composto | grafo com verificação, sem cauda opcional |\r\n| `autonomous` | problema amplo (5/5 ou 3+ domínios) | grafo + healing + replan + verificação final |\r\n\r\n`--mode` força o modo. Sem override, um teto `--max-cost` faz o plano **degradar** de modo em vez de estourar o orçamento em silêncio.\r\n\r\n### Inteligência assimétrica\r\n\r\nCada tarefa recebe o modelo do seu papel, não o modelo do run: `commander` (tier premium) planeja e coordena, `specialist` (balanced) executa, `worker` (fast) faz extração, formatação e validação. Uma retentativa **escala** o papel em vez de repetir o modelo que já falhou. Fixe modelos por papel em `.izanagi/izanagi.config.json`:\r\n\r\n```json\r\n{ \"roles\": { \"commander\": { \"model\": \"claude-opus-4-1\" },\r\n             \"specialist\": { \"model\": \"claude-sonnet-4-5\" },\r\n             \"worker\": { \"model\": \"gemini-2.0-flash\" } } }\r\n```\r\n\r\n### Verificação por evidência\r\n\r\nNenhuma tarefa termina porque o agente disse que terminou. Cada contrato carrega critérios de aceite derivados do schema real do artefato **e os que o usuário declarou** (`--acceptance`), e a Verification Engine devolve `VERIFIED`, `FAILED` ou `UNVERIFIED`. Com `--verify-tests`, um dos critérios é o **exit code** do comando de teste do projeto: a única camada do runtime que decide por execução, e não por leitura de texto. Critério semântico é julgado por um modelo barato (papel `worker`, artefato resumido); com `--no-judge`, ou sem provider, ele **nunca vira aprovação**: fica `UNVERIFIED`, e o run reporta isso. Juiz que não conseguiu decidir também não reprova.\r\n\r\nCom `--prompt-only`, apenas compila `izanagi-prompt.md` para colar manualmente em outra ferramenta, sem executar nada. Nós de aprovação (`human-in-the-loop`) pausam a execução até `izanagi approve <run-id>`.\r\n\r\n### O run lê o projeto e entrega arquivo\r\n\r\nDois nós do plano não chamam modelo nenhum: eles passam pela `ToolRegistry`, com permissão declarada no contrato, trust tier pela origem e política aplicada **antes** de executar.\r\n\r\n| Nó | Quando | Permissão | O que faz |\r\n|---|---|---|---|\r\n| `survey` | default num diretório com manifesto reconhecido; `--no-survey` desliga | `fs:read` | Levanta stack, manifestos, árvore por extensão, entrypoints e o começo do README. O resultado entra no contexto mínimo das tarefas raiz |\r\n| `materialize` | `--output <dir>`, e só quando o plano produz artefato que pode carregar código | `fs:write` | Escreve os arquivos que o agente declarou (`### FILE: <caminho>` + bloco de código) em `<output>/<slug>/` |\r\n| `deliver` | `--output <dir>` | `fs:write` | Grava o que o run produziu num documento único dentro do projeto |\r\n\r\nNenhum nó de agente recebe permissão nenhuma: um agente não escreve, não lê arquivo e não executa comando. Há teste que percorre o plano inteiro conferindo isso nó a nó.\r\n\r\nO survey existe porque a alternativa era pior e invisível: um agente escrevia sobre um projeto que nunca viu, inventava a stack e os caminhos, e o artefato passava na verificação — o schema pergunta se os campos existem, não se correspondem a alguma realidade. O levantamento é determinístico (não custa token), tem teto de profundidade e de entradas, e **declara o próprio corte**. Só as raízes do grafo dependem dele: repetir o mesmo levantamento em sete prompts seria a duplicação de contexto que a arquitetura proíbe.\r\n\r\nA materialização tem uma fronteira que a torna defensável: os arquivos vão para um subdiretório da saída, **nunca por cima do código do projeto**. Aplicar sobre a fonte exigiria uma garantia que nenhuma verificação determinística consegue dar hoje; quem quer aplicar revisa e copia — e é aí que uma pessoa olha o diff. A escrita é **tudo ou nada**: a validação roda sobre o manifesto inteiro antes de qualquer arquivo tocar o disco, porque \"6 arquivos escritos, 3 recusados\" é o relatório que engana. Arquivo vazio, caminho absoluto, escape de diretório e marca de trabalho não feito (`TODO`, `FIXME`, `implement later`) recusam o manifesto inteiro.\r\n\r\nA entrega muda o que a verificação significa. Um critério `file-exists` sobre um arquivo que ninguém escreveu passa quando o arquivo já existia por outro motivo; aqui o arquivo é gravado pela `ToolRegistry` e conferido depois, então o critério passa a significar \"o runtime gravou isto\". O nome do arquivo sai do objetivo, então repetir o mesmo objetivo reescreve a mesma entrega em vez de acumular um arquivo por execução — entrega é produto, e o histórico continua em `.izanagi/state/`.\r\n\r\n### SDK\r\n\r\n```ts\r\nimport { izanagi } from 'izanagi-ai';\r\n\r\n// Estimar antes de gastar: nenhum token é consumido aqui.\r\nconst plan = izanagi.plan({ objective: 'auditar a API de login' });\r\nconsole.log(plan?.mode, plan?.estimate.maxCostUsd);\r\n\r\nconst run = izanagi.run({\r\n  objective: 'auditar a API de login',\r\n  budget: { maxCost: 0.5 },\r\n  output: 'docs',   // grava a entrega em <baseDir>/docs; fora da raiz, run() rejeita antes de planejar\r\n  // survey: false  // default: ligado quando baseDir tem manifesto reconhecido\r\n});\r\nrun.on('task:start', (e) => console.log(e.data));\r\nconst result = await run;\r\nconsole.log(result.status, result.telemetry?.estimatedCostUsd, result.verification);\r\nconsole.log(result.deliveredTo);  // só presente quando a gravação REALMENTE aconteceu\r\n```\r\n\r\n---\r\n\r\n## Arquitetura Poliglota\r\n\r\nO crescimento novo vive numa topologia poliglota que coexiste com o runtime npm legado em padrão Strangler Fig (ADR-001): contratos IPC, error codes e env vars canônicos em [`docs/POLYGLOT.md`](docs/POLYGLOT.md).\r\n\r\n| Componente | Linguagem | O que faz | Como testar |\r\n|---|---|---|---|\r\n| `crates/izanagi_core` | Rust | Quality engine: 7 heurísticas anti-slop sobre TS/Python/Go; protocolo NDJSON stdin/stdout (`validate`/`rules`/`version`) + op `scan-rationalizations`; bindings WASM feature-gated | `cargo test --workspace` (126 testes declarados no fonte) |\r\n| `crates/izanagi_mcp` | Rust | Cliente MCP JSON-RPC 2.0 sobre stdio: discovery + invocação pontual (`izanagi-mcp call --tool=<name>`) | incluso no `cargo test --workspace` |\r\n| `go-services/swarm_orchestrator` | Go | Orquestrador de swarm (Uber Fx): pipeline architect→engineer→qa→security via JSON-RPC 2.0 sobre UDS com event push | `go build ./... && go vet ./... && go test ./...` |\r\n| `python-engine/ast_analyzer` | Python ≥ 3.10 | Análise semântica multilíngue: símbolos, complexidade ciclomática, imports (tree-sitter + fallback estrutural) | `.venv/bin/python -m pytest tests/ -q` (41 testes) |\r\n| `packages/sdk` (`@izanagi/sdk`) | TypeScript | Clientes tipados strict para os 4 núcleos + catálogo de skills; zero dependências de runtime | `npm test` dentro de `packages/sdk` (42 testes) |\r\n| `packages/cli` (`izanagi-next`) | TypeScript | CLI de nova geração: run em 4 fases com auto-heal (N=2) + gate anti-racionalização; `agent list`, `skill list/show --ref`, `gates check` | `npm test` dentro de `packages/cli` (13 testes) |\r\n\r\nDiagnóstico rápido de todos os componentes:\r\n\r\n```bash\r\nizanagi polyglot status          # saúde dos núcleos poliglotas (--json | --strict)\r\nnode packages/agent-migrator/cli.mjs --check   # drift YAML ↔ JSON dos agentes\r\nnode packages/skill-migrator/cli.mjs --dry-run # valida migração skills v1 → v2 sem escrever\r\n```\r\n\r\n### Estrutura do Repositório\r\n\r\n```text\r\nizanagi-ai/\r\n├── bin/                        Executável da CLI legado (bin/izanagi.js → dist/cli)\r\n├── src/                        Runtime real em TypeScript (orchestrator, evaluation, resolver, scanner, factories, tools, tracer, llm, cli)\r\n├── core/                       Engines (.md) + skill-resolver.json (aliases → targets + compositions)\r\n├── agents/                     22 definições de agentes em JSON (fonte da verdade dos comandos)\r\n├── skills/                     Skills legado v1 (skills/<name>/SKILL.md + references.md opcional)\r\n├── .skills/                    Catálogo ativo v2 (.skills/<name>/SKILL.md + references/)\r\n├── crates/                     Rust: izanagi_core (quality engine + WASM) e izanagi_mcp (cliente MCP stdio)\r\n├── go-services/swarm_orchestrator/  Orquestrador de swarm em Go (Uber Fx, JSON-RPC 2.0 sobre UDS)\r\n├── python-engine/              Analisador AST multilíngue (tree-sitter + fallback estrutural)\r\n├── packages/                   sdk (@izanagi/sdk) · cli (izanagi-next) · agent-migrator · skill-migrator\r\n├── references/                 Curadoria de referências reais por domínio (webgl-3d, scrollytelling, stack-2026...)\r\n├── .agents/memoria/            Memória persistente anti-repetição (contexto, decisoes, erros-corrigidos, learnings)\r\n├── .opencode/                  Comandos slash do Opencode (adapters em .claude/, .codex/, .cursor/...)\r\n├── docs/POLYGLOT.md            Contratos IPC, error codes, env vars e resumo dos ADRs\r\n├── AGENTS.md                   Instruções de operação do framework\r\n├── ARCHITECTURE.md             Visão arquitetural\r\n├── SYSTEM.md                   Fundação do sistema (arquitetura real do runtime)\r\n└── RULES.md                    Regras operacionais (Anti-Generic High-Craft & Cinematic UI)\r\n```\r\n\r\n---\r\n\r\n## Comandos Principais da CLI\r\n\r\nCLI legado (`izanagi`, publicada no npm):\r\n\r\n| Comando | Descrição |\r\n|---|---|\r\n| `izanagi init [dir] [--packs a,b,c]` | Cria projeto com `.agents/` e seleção de packs de skills. |\r\n| `izanagi run [agent] --task \"<task>\"` | Commander decide o modo, roteia por papel, executa o grafo, verifica contra os critérios de aceite e persiste trace + telemetria de custo. Flags: `--mode direct\\|assisted\\|orchestrated\\|autonomous`, `--budget N`, `--max-cost N`, `--model <id>`, `--local` (só providers locais, e serializa o pool: GPU única não ganha com paralelismo), `--max-concurrency N` (teto de tarefas em voo), `--cache`, `--output <dir>` (grava a entrega no projeto), `--survey` / `--no-survey` (força ou desliga o levantamento do projeto antes de decidir), `--acceptance \"<critério>\"` (repetível: o que a ENTREGA precisa cumprir, além do schema), `--verify-tests` (roda o comando de teste do projeto no fim do grafo e a métrica de teste passa a vir do exit code), `--min-quality 0..1` (compara estratégias e escolhe a mais barata que atinge o piso de VERIFICAÇÃO), `--reuse-artifacts` (reaproveita artefato de run anterior com a mesma pergunta), `--allow-tool <id>` (allowlist de tools do run), `--agent-tools none\\|read\\|write` (política de tools do EXECUTOR de processo, diferente de `--allow-tool`: aqui se decide se o subprocesso do agente lê o repositório ou altera arquivos). **Ctrl-C cancela o run** em vez de matar o processo: o batch em voo é abortado, o progresso já gravado fica no checkpoint e `izanagi resume <run-id>` retoma dali, `--no-commander` (planejamento legado por categoria), `--no-judge` (desliga o juiz semantico), `--prompt-only`. |\r\n| `izanagi models [--json]` | Catálogo de modelos, providers configurados e qual modelo cada papel (commander/specialist/worker) receberia agora, com custo por 10k tokens. |\r\n| `izanagi budget [run-id] [--json]` | Para onde foi o orçamento daquele run: tokens por fase, custo estimado, cache local e do provider, contexto poupado, escaladas, degradação e verificação por tarefa. |\r\n| `izanagi chat` | REPL interativo da CLI. |\r\n| `izanagi dashboard [--port N]` | Dashboard local (Run Explorer, Arena, Memory). |\r\n| `izanagi agent create \"<requisito>\" [--name=slug] [--skills=a,b]` | Agent Factory: gera agente com genome completo em `agents/generated/` (detecta lacuna vs. 22 core). |\r\n| `izanagi agent list \\| inspect <name>` | Lista/inspeta agentes (inclui `agents/generated/`) com genome. |\r\n| `izanagi skill create <nome> --gap=\"<descrição>\" [--force]` | Skill Factory: cria skill com frontmatter, security scan pré-escrita e recusa de lacuna já coberta. |\r\n| `izanagi skill list \\| search <q> \\| inspect <name>` | Lista, busca e detalha skills (catálogo v2, com progressive disclosure). |\r\n| `izanagi create <agent\\|skill> <name>` | Cria scaffold cru de agente (JSON) ou skill (SKILL.md), sem validação. |\r\n| `izanagi compile <agente> [arquivo]` | Compila um System Prompt completo do agente + fundação do sistema. |\r\n| `izanagi workflow list \\| inspect <template>` | Templates de grafo de execução por categoria (10). |\r\n| `izanagi eval <file.json> \\| --metrics ... \\| --report <run-id>` | Evaluation Engine: métricas ponderadas + veredito (PASS/.../UNKNOWN). |\r\n| `izanagi benchmark [run\\|tokens\\|compare]` | 10 benchmarks builtin + comparação de regressões entre builds. `tokens` compara o plano do runtime legado com o do Commander (chamadas, tokens e custo, de forma determinística). Alias histórico: `arena`. |\r\n| `izanagi trace [run-id]` | Traces de execução (spans, healing, graph, avaliação). |\r\n| `izanagi memory inspect \\| search <q>` | Estado da memória de execução e busca em `.agents/memoria/`. |\r\n| `izanagi polyglot status [--json\\|--strict]` | Saúde dos núcleos poliglotas (Rust, Go, Python, packages TS): checagens de existência + probes baratos; `--strict` sai com código 1 se algo estiver ausente. |\r\n| `izanagi doctor [--deep]` | Auditoria de integridade; `--deep` adiciona security scan das skills. |\r\n| `izanagi diagnose` | Diagnóstico profundo do runtime (state, agent genome, contratos de artifact). |\r\n| `izanagi resume <run-id>` | Retoma execução interrompida (crash) ou pausada a partir do checkpoint: sem replanejar nem reexecutar nós concluídos. |\r\n| `izanagi approve <run-id> [node-id]` | Aprova uma ação de alto risco pausada (nó `kind: 'approval'`) e retoma. |\r\n| `izanagi reject <run-id> [node-id] [--reason]` | Rejeita a ação pausada (o nó falha com o motivo) e retoma: self-healing/abort seguem normalmente. |\r\n| `izanagi explain <run-id>` | Por que o Izanagi decidiu isso: decisões (Decision Journal) + conversa entre agentes + self-healing + veredito, sem chain-of-thought. `--artifacts` mostra o conteúdo produzido, `--conversation` o log A2A inteiro. |\r\n| `izanagi export --cli <cli>` | Regenera adapters multi-CLI (opencode, claude, codex, cursor, copilot, kimi, all). Idempotente. |\r\n| `izanagi --version` | Exibe a versão da CLI. |\r\n\r\nCLI de nova geração (`izanagi-next`, em `packages/cli`, requer Node ≥ 22): pipeline de agentes sobre os núcleos poliglotas, com gate anti-racionalização via Rust core e auto-heal (N=2 tentativas) no run em 4 fases.\r\n\r\n```bash\r\ncd packages/cli && npm install && npm run build\r\nnode dist/cli/src/index.js run --agent=architect --task=\"Design a caching layer\"\r\nnode dist/cli/src/index.js agent list\r\nnode dist/cli/src/index.js skill list --category=rust   # ou --search=<termo>\r\nnode dist/cli/src/index.js skill show <nome> --ref=<arquivo>\r\nnode dist/cli/src/index.js gates check <file>\r\n```\r\n\r\n---\r\n\r\n## Skills & Agentes\r\n\r\n**23 agentes especializados** (`agents/*.json`, fonte da verdade): `/orchestrator`, `/discovery`, `/product-reasoner`, `/architect`, `/senior-engineer`, `/ai-engineer`, `/techlead`, `/automation-engineer`, `/security`, `/devops`, `/database`, `/qa`, `/bug-hunter`, `/docs`, `/pm`, `/professor`, `/researcher`, `/evaluator`, `/adversarial-critic`, `/form-engineer`, `/animation`, `/agent-architect`, `/skill-architect`. Cada um carrega um Agent Genome de 13 campos e chains compostas; a tabela completa com papéis está em [`AGENTS.md`](AGENTS.md).\r\n\r\n**Skills**: 106 módulos legado v1 (`skills/`) e o catálogo ativo **v2** (`.skills/<name>/SKILL.md`), ambos distribuídos no pacote npm. O formato v2 usa front-matter estruturado:\r\n\r\n```yaml\r\n---\r\nname: \"anti-ai-slop\"\r\ndescription: \"Detecta e corrige design 'cara de IA'...\"\r\nversion: 2.0.0\r\ncategory: design\r\ntools:\r\n  mcp:\r\n    - mcp:fs_read\r\nreferences:\r\n  - \"references.md\"\r\n---\r\n```\r\n\r\nSeguido de seções fixas: *Triggering Criteria*, *Step-by-Step Workflow*, *Verification Steps*, *Common Rationalizations* e *Red Flags*. O consumo é por **progressive disclosure** (`izanagi skill inspect`, ou `izanagi-next skill show`, carrega só o módulo necessário); skills nunca rodam isoladas — encadeiam via `compositions` do `core/skill-resolver.json` (258 aliases, 16 composições).\r\n\r\n---\r\n\r\n## Desenvolvimento\r\n\r\nOrdem importa: `dist/` é gitignored e `bin/izanagi.js` importa de `../dist/cli/index.js` — rode `npm run build` antes de qualquer comando CLI local (`doctor`, `polyglot status`, `export`...), senão roda código obsoleto ou quebra. O mesmo vale para `packages/*/dist`.\r\n\r\n```bash\r\n# Legado npm (raiz)\r\nnpm install\r\nnpm run build       # tsc && node dist/scripts/generate-manifest.js\r\nnpm test            # build + node --test dist/runtime/tests/*.test.js (966 testes)\r\nnpm run verify      # build + teste de instalação em sandbox (passa todos os pack IDs)\r\nnpm run doctor      # node bin/izanagi.js doctor [--deep]\r\n\r\n# Núcleos poliglotas\r\ncargo test --workspace                                        # Rust: core + mcp (126 testes declarados no fonte)\r\ncargo check -p izanagi_core --features wasm                   # type-check dos bindings WASM\r\n(cd go-services/swarm_orchestrator && go build ./... && go vet ./... && go test ./...)\r\n(cd python-engine && python -m venv .venv && .venv/bin/python -m pip install -r requirements-dev.txt)  # o venv NAO e versionado\r\n(cd python-engine && .venv/bin/python -m pytest tests/ -q)     # 41 testes\r\n(cd packages/sdk && npm install && npm test)                  # 42 testes\r\n(cd packages/cli && npm install && npm test)                  # 13 testes\r\n```\r\n\r\nRequisitos por componente: Node ≥ 18 (raiz) e ≥ 22 nos pacotes novos, Rust stable, Go 1.26, Python ≥ 3.10.\r\n\r\n### Publicando no NPM\r\n\r\nCD exclusivo de tag `v*` (`.github/workflows/publish.yml`): bump → commit → tag → push; o workflow publica com provenance OIDC (SLSA v1). Localmente, o fluxo manual permanece:\r\n\r\n```bash\r\nnpm run bump:patch   # ou bump:minor / bump:major\r\nnpm publish          # prepublishOnly roda o build automaticamente\r\n```\r\n\r\nCI (`.github/workflows/polyglot.yml`): 6 jobs paralelos em push/PR para `main` — legacy-npm, rust (clippy+test+wasm check), wasm-build E2E, go, python, ts-packages.\r\n\r\n---\r\n\r\n## Trabalho agendado (sem servidor)\r\n\r\nO Izanagi é local-first por decisão: não existe daemon, porta escutando nem credencial em repouso. Quem agenda é o cron ou o Task Scheduler do sistema.\r\n\r\n```bash\r\nizanagi run \"auditar dependências e abrir relatório\" --json --notify-webhook=https://exemplo/hook\r\n```\r\n\r\n| | |\r\n|---|---|\r\n| `--json` | Um único objeto JSON no stdout. A saída humana é silenciada; `console.error` continua vivo, porque erro real precisa chegar ao stderr do agendador. |\r\n| código de saída | `0` concluiu · `1` falhou · `2` aguarda decisão humana. Aguardar aprovação não é falha e não deve alertar como falha. |\r\n| `--notify-webhook=<url>` | POST de fim de run, uma retentativa. `4xx` não é repetido (configuração errada não melhora repetindo), `5xx` é. Falha de notificação nunca derruba o run. |\r\n\r\nO webhook leva **metadado**: status, score, tokens, custo, verificação por tarefa e nomes de artefato. **Nunca o conteúdo produzido** — um endpoint de notificação costuma ser um canal de equipe ou um serviço que ninguém auditou. Para o conteúdo, `izanagi explain <run-id> --artifacts`, na máquina onde o run aconteceu.\r\n\r\n## Documentação\r\n\r\n| Documento | Conteúdo |\r\n|---|---|\r\n| [`AGENTS.md`](AGENTS.md) | Reference operacional: os 23 agentes, comandos, gotchas de desenvolvimento e release flow. |\r\n| [`docs/POLYGLOT.md`](docs/POLYGLOT.md) | Contratos IPC entre núcleos, error codes JSON-RPC, tabela de env vars, gaps conhecidos e resumo dos ADRs. |\r\n| [`docs/HANDOFF.md`](docs/HANDOFF.md) | Passagem completa da rearquitetura v3.13.0 → v3.18.0: o que mudou, onde cada coisa vive, decisões e por quê, bugs encontrados, números medidos e por onde continuar. **Comece por aqui** se pegou o repositório sem contexto. |\r\n| [`docs/RUNTIME-PENDING.md`](docs/RUNTIME-PENDING.md) | Nenhum item aberto: a tabela do que foi fechado, em qual commit e como, mais as limitações que são escolha com motivo registrado. |\r\n| [`ARCHITECTURE.md`](ARCHITECTURE.md) | Visão arquitetural do framework e da topologia poliglota. |\r\n| [`CONTRIBUTING.md`](CONTRIBUTING.md) | Guia de contribuição: convenções, fluxo de PR e padrões do repo. |\r\n| [`ROADMAP.md`](ROADMAP.md) | Planejamento de evolução por waves e marcos. |\r\n| [`SYSTEM.md`](SYSTEM.md) / [`RULES.md`](RULES.md) | Fundação do runtime e regras operacionais (Anti-Generic High-Craft & Cinematic UI). |\r\n| [`CHANGELOG.md`](CHANGELOG.md) | Histórico de versões. |\r\n\r\n---\r\n\r\n## Licença\r\n\r\nMIT: Use, modifique, distribua. Apenas mantenha os créditos.\r\n","readmeFilename":"README.md"}