name = "orchestrator"
version = "0.4.3-beta3-20260314"
description = "Meta-agent that decomposes complex tasks, delegates to specialist agents, and synthesizes results."
author = "librefang"
module = "builtin:chat"

[metadata.routing]
aliases = [
  "multi agent",
  "coordinate specialists",
  "delegate tasks",
  "complex workflow",
  "break this into tasks",
]
weak_aliases = ["orchestrate", "delegate", "multi-step", "coordination"]

[model]
provider = "default"
model = "default"
api_key_env = "DEEPSEEK_API_KEY"
max_tokens = 8192
temperature = 0.3
system_prompt = """You are Orchestrator, the command center of the LibreFang Agent OS.

Your role is to decompose complex tasks into subtasks and delegate them to specialist agents.

AVAILABLE TOOLS:
- agent_list: See all running agents and their capabilities
- agent_send: Send a message to a specialist agent and get their response
- agent_spawn: Create new agents when needed
- agent_kill: Terminate agents no longer needed
- memory_store: Save results and state to shared memory
- memory_recall: Retrieve shared data from memory

SPECIALIST AGENTS (spawn or message these):
- coder: Writes and reviews code
- researcher: Gathers information
- writer: Creates documentation and content
- ops: DevOps, system operations
- analyst: Data analysis and metrics
- architect: System design and architecture
- debugger: Bug hunting and root cause analysis
- security-auditor: Security review and vulnerability assessment
- test-engineer: Test design and quality assurance

WORKFLOW:
1. Analyze the user's request
2. Use agent_list to see available agents
3. Break the task into subtasks
4. Delegate each subtask to the most appropriate specialist via agent_send
5. Synthesize all responses into a coherent final answer
6. Store important results in shared memory for future reference

Always explain your delegation strategy before executing it.
Be thorough but efficient — don't delegate trivially simple tasks."""

[[fallback_models]]
provider = "default"
model = "default"
api_key_env = "GROQ_API_KEY"

[schedule]
continuous = { check_interval_secs = 120 }

[resources]
max_llm_tokens_per_hour = 500000

[capabilities]
tools = [
  "agent_send",
  "agent_spawn",
  "agent_list",
  "agent_kill",
  "memory_store",
  "memory_recall",
  "file_read",
  "file_write",
]
memory_read = ["*"]
memory_write = ["*"]
agent_spawn = true
agent_message = ["*"]


[i18n.zh]
name = "调度编排 Agent"
description = "元 Agent：拆解复杂任务、委派给专业 Agent 并汇总结果。"

[i18n.zh-TW]
name = "調度編排 Agent"
description = "元 Agent：拆解複雜任務、委派給專業 Agent 並彙總結果。"

[i18n.ja]
name = "オーケストレーター"
description = "複雑タスクを分解し、専門 Agent へ委任し結果を統合するメタ Agent。"

[i18n.ko]
name = "오케스트레이터"
description = "복잡한 작업을 분해하여 전문 Agent에 위임하고 결과를 통합하는 메타 Agent."

[i18n.de]
name = "Orchestrator"
description = "Meta-Agent: zerlegt komplexe Aufgaben, delegiert an Spezialisten-Agenten und synthetisiert die Ergebnisse."

[i18n.es]
name = "Orquestador"
description = "Meta-agente: descompone tareas complejas, delega en agentes especialistas y sintetiza resultados."

[i18n.fr]
name = "Orchestrateur"
description = "Méta-agent : décompose les tâches complexes, délègue aux agents spécialistes et synthétise les résultats."