autonomous-loops

Autonomous Claude Code loops use pre-defined architectural patterns to script sequential pipelines or parallel multi-agent DAG orchestration for continuous development without manual intervention. This skill provides six proven loop patterns ranging from simple daily dev tasks to complex RFC-driven workflows.

Multi-agent DAG orchestration coordinates parallel agents working on interdependent work units for large feature rollouts within CI/CD pipelines. You need it when coordinating complex parallel projects that require conflict-free merge queue coordination and context persistence across iterations.

Yes, autonomous loop workflows support continuous PR iteration loops with built-in CI failure recovery patterns. The workflow automatically runs tests and lint checks, fixes CI failures, and produces ready-to-merge PRs from a written feature spec without manual intervention.

Yes, the workflow automation includes built-in context persistence strategies across iterations to support end-to-end autonomous development. It also provides quality gate implementations and merge coordination logic to maintain state across parallel agents and sequential pipeline runs.

The best way to coordinate parallel agents on interdependent features is using DAG orchestration patterns with merge queue coordination for conflict-free parallel work. This skill provides pre-vetted loop patterns that handle quality cleanup passes and merge coordination automatically.

Autonomous development loops often fail during merge coordination due to missing conflict-free merge queue logic or inadequate quality gate implementations. This skill provides pre-defined merge coordination patterns and quality cleanup passes to ensure parallel agents can merge interdependent work units without conflicts.