Agent orchestrator
Unified skill library for Claude, Codex, Cursor, Antigravity & AI agents — 2,658 skills across 15 domains
npx -y skills add sinhoneyy/master-skills --skill agent-orchestratorAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 9 stars9 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.
SKILL.md
9.6 KB, as published. Nobody here has run it
Agent Orchestrator
Overview
Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.
When to Use This Skill
- When you need specialized assistance with this domain
Do Not Use This Skill When
- The task is unrelated to agent orchestrator
- A simpler, more specific tool can handle the request
- The user needs general-purpose assistance without domain expertise
How It Works
Meta-skill que funciona como camada central de decisao e coordenacao para todo o ecossistema de skills. Faz varredura automatica, identifica agentes relevantes e orquestra multiplos skills para tarefas complexas.
Principio: Zero Intervencao Manual
- SEMPRE faz varredura antes de processar qualquer solicitacao
- Novas skills sao auto-detectadas e incluidas ao criar SKILL.md em qualquer subpasta
- Skills removidas sao auto-excluidas do registry
- Nenhum comando manual e necessario para registrar novas skills
Workflow Obrigatorio (Toda Solicitacao)
Execute estes passos ANTES de processar qualquer request do usuario. Os scripts usam paths relativos automaticamente - funciona de qualquer diretorio.
Passo 1: Auto-Discovery (Varredura)
python agent-orchestrator/scripts/scan_registry.py
Ultra-rapido (<100ms) via cache de hashes MD5. So re-processa arquivos alterados. Retorna JSON com resumo de todos os skills encontrados.
Passo 2: Match De Skills
python agent-orchestrator/scripts/match_skills.py "<solicitacao do usuario>"
Retorna JSON com skills ranqueadas por relevancia. Interpretar o resultado:
| Resultado | Acao |
|---|---|
matched: 0 | Nenhum skill relevante. Operar normalmente sem skills. |
matched: 1 | Um skill relevante. Carregar seu SKILL.md e seguir. |
matched: 2+ | Multiplos skills. Executar Passo 3 (orquestracao). |
Passo 3: Orquestracao (Se Matched >= 2)
python agent-orchestrator/scripts/orchestrate.py --skills skill1,skill2 --query "<solicitacao>"
Retorna plano de execucao com padrao, ordem dos steps e data flow entre skills.
Passo Rapido (Atalho)
Para queries simples, os passos 1+2 podem ser combinados em sequencia:
python agent-orchestrator/scripts/scan_registry.py && python agent-orchestrator/scripts/match_skills.py "<solicitacao>"
Skill Registry
O registry vive em:
agent-orchestrator/data/registry.json
Locais De Busca
O scanner procura SKILL.md em:
.claude/skills/*/(skills registradas no Claude Code)*/(skills standalone no top-level)*/*\(skills em subpastas, ate profundidade 3)
Metadata Por Skill
Cada entrada no registry contem:
| Campo | Descricao |
|---|---|
| name | Nome da skill (do frontmatter YAML) |
| description | Descricao completa (triggers inclusos) |
| location | Caminho absoluto do diretorio |
| skill_md | Caminho absoluto do SKILL.md |
| registered | Se esta em .claude/skills/ (true/false) |
| capabilities | Tags de capacidade (auto-extraidas + explicitas) |
| triggers | Keywords de ativacao extraidas da description |
| language | Linguagem principal (python/nodejs/bash/none) |
| status | active / incomplete / missing |
Comandos Do Registry
## Scan Rapido (Usa Cache De Hashes)
python agent-orchestrator/scripts/scan_registry.py
## Tabela De Status Detalhada
python agent-orchestrator/scripts/scan_registry.py --status
## Re-Scan Completo (Ignora Cache)
python agent-orchestrator/scripts/scan_registry.py --force
Algoritmo De Matching
Para cada solicitacao, o matcher pontua skills usando:
| Criterio | Pontos | Exemplo |
|---|---|---|
| Nome do skill na query | +15 | "use web-scraper" -> web-scraper |
| Keyword trigger exata | +10 | "scrape" -> web-scraper |
| Categoria de capacidade | +5 | data-extraction -> web-scraper |
| Sobreposicao de palavras | +1 | Palavras da query na description |
| Boost de projeto | +20 | Skill atribuida ao projeto ativo |
Threshold minimo: 5 pontos. Skills abaixo disso sao ignoradas.
Match Com Projeto
python agent-orchestrator/scripts/match_skills.py --project meu-projeto "query aqui"
Skills atribuidas ao projeto recebem +20 de boost automatico.
Padroes De Orquestracao
Quando multiplos skills sao relevantes, o orchestrator classifica o padrao:
1. Pipeline Sequencial
Skills formam uma cadeia onde o output de uma alimenta a proxima.
Quando: Mix de skills "produtoras" (data-extraction, government-data) e "consumidoras" (messaging, social-media).
Exemplo: web-scraper coleta precos -> whatsapp-cloud-api envia alerta
user_query -> web-scraper -> whatsapp-cloud-api -> result
2. Execucao Paralela
Skills trabalham independentemente em aspectos diferentes da solicitacao.
Quando: Todas as skills tem o mesmo papel (todas produtoras ou todas consumidoras).
Exemplo: instagram publica post + whatsapp envia notificacao (ambos recebem o mesmo conteudo)
user_query -> [instagram, whatsapp-cloud-api] -> aggregated_result
3. Primario + Suporte
Uma skill principal lidera; outras fornecem dados de apoio.
Quando: Uma skill tem score muito superior as demais (>= 2x).
Exemplo: whatsapp-cloud-api envia mensagem (primario) + web-scraper fornece dados (suporte)
user_query -> whatsapp-cloud-api (primary) + web-scraper (support) -> result
Detalhes Em References/Orchestration-Patterns.Md
Gerenciamento De Projetos
Atribuir skills a projetos permite boost de relevancia e contexto persistente.
Arquivo De Projetos
agent-orchestrator/data/projects.json
Operacoes
Criar projeto: Adicionar entrada ao projects.json:
{
"name": "nome-do-projeto",
"created_at": "2026-02-25T12:00:00",
"skills": ["web-scraper", "whatsapp-cloud-api"],
"description": "Descricao do projeto"
}
Adicionar skill a projeto: Atualizar o array skills do projeto.
Remover skill de projeto: Remover do array skills.
Consultar skills do projeto: Ler o projects.json e listar skills atribuidas.
Adicionando Novas Skills
Para adicionar uma nova skill ao ecossistema:
- Criar uma pasta em qualquer lugar sob
skills root: - Criar um
SKILL.mdcom frontmatter YAML:
---
name: minha-nova-skill
description: "Descricao com keywords de ativacao..."
---
## Documentacao Da Skill
- Pronto! O auto-discovery detecta automaticamente na proxima solicitacao.
Opcionalmente, para discovery nativo do Claude Code:
4. Copiar o SKILL.md para .claude/skills/<nome>/SKILL.md
Tags De Capacidade Explicitas (Opcional)
Adicionar ao frontmatter para matching mais preciso:
capabilities: [data-extraction, web-automation]
Ver Status De Todos Os Skills
python agent-orchestrator/scripts/scan_registry.py --status
Interpretar Status
| Status | Significado |
|---|---|
| active | SKILL.md com name + description presentes |
| incomplete | SKILL.md existe mas falta name ou description |
| missing | Diretorio existe mas sem SKILL.md |
Skills Atuais Do Ecossistema
| Skill | Capacidades | Status |
|---|---|---|
| web-scraper | data-extraction, web-automation | active |
| junta-leiloeiros | government-data, data-extraction | active |
| whatsapp-cloud-api | messaging, api-integration | active |
| social-media, api-integration | partial |
Esta tabela e atualizada automaticamente via scan_registry.py --status.
Best Practices
- Provide clear, specific context about your project and requirements
- Review all suggestions before applying them to production code
- Combine with other complementary skills for comprehensive analysis
Common Pitfalls
- Using this skill for tasks outside its domain expertise
- Applying recommendations without understanding your specific context
- Not providing enough project context for accurate analysis
Related Skills
multi-advisor- Complementary skill for enhanced analysistask-intelligence- Complementary skill for enhanced analysis
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Gives 0 of the 12 instructions most agent orchestration skills give
Counted across 742 of the 995 authors here whose files we hold, read 2026-08-06
- run the full test suite after integrating changesin 53 of 742, across 20 files
- reference existing artifacts by path or URLin 52 of 742, across 22 files
- dispatch one agent per independent problem domainin 50 of 742, across 17 files
- verify fixes do not conflictin 45 of 742, across 13 files
- include a suggested skills section in the documentin 45 of 742, across 15 files
- redact sensitive informationin 41 of 742, across 11 files
- save to the temporary directory of the operating systemin 39 of 742, across 9 files
- tailor the document to user-provided focus argumentsin 39 of 742, across 9 files
- spot check agent changes for systematic errorsin 34 of 742, across 7 files
- write a handoff document summarising the current conversationin 31 of 742, across 6 files
- assign each agent a specific scopein 23 of 742, across 8 files
- provide specific scope and clear goalin 23 of 742, across 5 files
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.