EvanandClaude Opus 4.6
8f2244eb6f
* chore: remove router agent builtin:router has been replaced by LLM intent routing in the kernel. Assistant is now the sole entry point — see librefang/librefang#1336. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: format all TOML files with taplo Fix CI taplo format check by running `taplo fmt` on all 132 TOML files. --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
83 lines
2.3 KiB
TOML
83 lines
2.3 KiB
TOML
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 = ["*"]
|