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autopilotlisted

Continuous-operation mode for rockie — runs the experiment queue autonomously, using Zero-Cost Monitoring ($0 LLM cost during training), anti-burn exponential cooldown on failures, and ntfy to wake the human only when a decision is needed. Use when you want agent-driven research to proceed for days without human input. Not appropriate for unproven projects — only enable after you have a populated queue, budget ceilings, and a working launcher.
Rockielab/rockie-claude · ★ 20 · AI & Automation · score 76
Install: claude install-skill Rockielab/rockie-claude
# /autopilot — days-long autonomous operation This is the "just keep going while I sleep" mode. It composes the pieces you already have (queue, ZCM, journal, calibration, budget, dead-ends, [LEARN]) into a single daemon that can drive an 8×H100 project for a week without human input. ## Pre-flight checklist — DO NOT skip Before starting autopilot, you MUST: - [ ] Populate the queue. `queue.py status` shows ≥ target pending items. - [ ] Set a budget. `.claude/budget.toml` exists with project + session ceilings. - [ ] Have a launcher. `autopilot.conf` points at a `LAUNCHER_CMD` that takes a queue-item JSON on stdin, starts training in the background (nohup + &), and writes its PID + log paths. - [ ] Configure ntfy. `NTFY_TOPIC` is set; you've subscribed in the app. Autopilot will wake you via ntfy on anomalies, ceiling-cross, and cooldown. - [ ] A working dry-run gate. `dry_run_gate.sh list` shows sentinels for every training script the queue might reference. - [ ] `[DEAD-END]` registry is current. Any director you've already killed is in the registry — autopilot queue-refill won't re-propose it. ## The daemon ```bash nohup bash .claude/scripts/autopilot_loop.sh > .claude/memory/autopilot.log 2>&1 & ``` Stop: ```bash bash .claude/scripts/autopilot_loop.sh --stop ``` ## What the loop does ``` loop forever: item = queue.py next --json # atomic claim, $0 LLM cost if item is None: if queue_under_target: ntfy(tier=2, "queue empty") sleep 300