factory-ralph-loop

Automating iterative AI agent tasks requires a bounded loop that runs the agent repeatedly until a clear exit condition is met. This skill uses a deterministic spawn and observe cycle to execute tasks until completion.

Filesystem memory persists task state directly to the disk between each agent iteration. This allows subsequent runs to read previous progress, ensuring incremental advancement toward task completion without losing context.

Yes, you can use an AI loop to automatically fix lint errors and run tests. The loop iteratively executes the agent, applying filesystem memory to track resolved errors until all tests pass and lint issues are cleared.

Ensuring an AI agent loop terminates safely requires setting a fixed maximum iteration limit. This bounded approach prevents infinite loops while providing deterministic orchestration and safe termination if the task remains incomplete.

Yes, iterative loops work well for PRD-driven tasks by applying repeated agent runs to fulfill product requirements. The filesystem-backed memory tracks incremental development progress across multiple iterations until the PRD criteria are satisfied.