Agent Orchestrator
FreeAutomate multi-agent workflows with zero manual intervention.
Free · Opens the source repo
What Agent Orchestrator does
Agent Orchestrator is a meta-skill designed to streamline the orchestration of multiple agents within a skill ecosystem. It automates the scanning of available skills, matches them based on their capabilities, and coordinates complex workflows without requiring manual input from the user. This skill acts as a central decision-making layer, ensuring that the right agents are utilized for specific tasks, thus enhancing efficiency and productivity.
The orchestration process begins with an automatic discovery feature that scans for available skills in designated directories. This process is quick and efficient, utilizing a caching mechanism to avoid unnecessary reprocessing. Once the skills are identified, the system matches them against the user’s request, ranking their relevance based on a scoring algorithm that considers keywords, capabilities, and project context. This ensures that the most appropriate skills are selected for execution.
When multiple skills are matched, the orchestrator categorizes the workflow into one of three patterns: sequential pipelines, parallel execution, or primary-support relationships. This structured approach allows for a clear data flow and efficient task execution, whether the skills are working independently or in conjunction with one another. Users can also manage projects by assigning skills to specific projects, which can enhance the relevance of the skills based on the context of the project.
This skill is particularly useful for developers and designers who need to automate complex workflows involving multiple agents. It provides a robust framework for managing skills and ensures that users can leverage the full capabilities of their skill ecosystem without the overhead of manual configuration.
When to use it
Use this skill when you require automated orchestration of multiple agents for complex tasks.
When not to use it
Avoid using this skill for simple tasks that can be handled by a single tool or when general-purpose assistance is needed without domain expertise.
What you can build with it
Automating Data Collection
Use the Agent Orchestrator to automate a workflow that collects data from various sources and processes it through multiple agents.
Coordinating Marketing Campaigns
Orchestrate a series of marketing tasks by integrating different skills for social media posting and data analysis.
Managing Software Development Tasks
Streamline the development process by coordinating skills for code generation, testing, and deployment.
How to install Agent Orchestrator
View source1. Install with the skills CLI
npx skills add sickn33/agentic-awesome-skills/agent-orchestrator --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by sickn33Agent 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.
Frequently asked questions about Agent Orchestrator
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