Gabriel Koerich Orchestrator

The orchestrator uses an LLM-as-classifier to route each task to the best agent. This is a non-agentic call (--print) — fast and cheap, no tool access needed.

How It Works

1. route_task.sh sends the task title, body, labels, and the skills catalog to a lightweight LLM (default: claude --model haiku --print).
2. The router LLM returns JSON:

   {
     "executor": "claude",
     "model": "sonnet",
     "decompose": false,
     "reason": "why this agent/model",
     "profile": {
       "role": "DeFi Protocol Engineer",
       "skills": ["Solana", "Anchor"],
       "tools": ["Bash", "Edit", "Read"],
       "constraints": ["audit with sealevel attacks"]
     },
     "selected_skills": ["solana-best-practices"]
   }

3. Sanity checks run — e.g. warns if a backend task gets routed to claude, or a docs task to codex.
4. If the router fails, it falls back to config.yml's router.fallback_executor (default: codex).

Config

router:
  agent: "claude"           # which LLM does the routing
  model: "haiku"            # fast/cheap model for classification
  timeout_seconds: 120
  fallback_executor: "codex"  # safety net if routing fails
  disabled_agents:          # exclude agents from routing
    - opencode
  allowed_tools:            # default tool allowlist
    - yq
    - jq
    - bash
  default_skills:           # always included in routing
    - gh
    - git-worktree

Available Executors

Complexity-Based Model Selection

The router assigns a complexity level (simple, medium, complex) which maps to agent-specific models:

model_map:
  simple:
    claude: "haiku"
    codex: "gpt-4.1-mini"
  medium:
    claude: "sonnet"
    codex: "gpt-4.1"
  complex:
    claude: "opus"
    codex: "o3"

The routing prompt is in prompts/route.md. The router only classifies — it never touches code or files.