Autonomous Loop Patterns

Concept of the skill

An autonomous loop has six primitives: a trigger, a worker agent, a progress signal, a stop condition, durable state, and a safety cap.

Coverage

• Core primitives of an autonomous agent loop: trigger, worker agent, progress signal, stop condition, durable state, and safety cap.
• Pattern selection across bounded single-run loops, sentinel continuation loops, checkpoint-resume loops, and external supervisor loops.
• Completion signal design: explicit done markers, tracker state, exit status, persisted status files, and observable progress evidence.
• Safety design: iteration limits, consecutive-error limits, elapsed-time limits, budget limits, context-health exits, and human handoff thresholds.
• Stall detection and recovery: heartbeat age, unchanged work state, repeated failures, repeated plan churn, and supervisor escalation.
• Checkpoint and handoff contracts: what state must persist between runs and what state must never live only in agent memory.
• Anti-patterns that make autonomous loops unsafe: unbounded retry, prompt-only reliability, hidden mutable state, and silent respawn storms.

Philosophy of the skill

An autonomous agent loop is not just an agent being told to continue. It is a control system. The agent is one component; the loop decides when to run it again, what evidence proves progress, what state survives a crash, and when a human must take over.

The smallest safe loop is usually better than the most powerful loop. A one-off task with a clear finish condition does not need a queue supervisor. A multi-session backlog should not rely on a single completion word. A long-running unattended process must not depend on the worker agent remembering its own state.