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Autonomous Daemon

core/autonomous_daemon.py runs a continuous Perceive → Decide → Execute → Evaluate loop:
Each cycle:
  1. Perceive — read environment state, pending tasks, provider health
  2. Decide — route task to optimal node via MeshRouter
  3. Execute — run crew or single agent with governance pipeline
  4. Evaluate — Supervisor scores result; retry or escalate if needed
Cycle history: logs/daemon/cycles.jsonl

Task Routing

The mesh routes by task type to the primary node, with fallbacks in order:

Supervisor Scoring

Every task output is scored before acceptance:
Max retries: 2 (configurable in dof.constitution.yml)

Auto-Scaling

core/mesh_orchestrator.py computes a scaling decision every cycle:

MeshDaemon Configuration

Session state is persisted via core/session_resume.py — cycle count and improvements survive restarts.

Claude Commander — 5 Modes


Mesh Nodes

Node table and circuit breaker

Running the Mesh

Launch commands