What problem does it solve? Running Claude Code autonomously over many iterations requires choosing the right loop architecture, bridging context between isolated runs, and coordinating parallel agents without merge conflicts or quality degradation. ## Core Features & Use Cases - Loop Pattern Spectrum: Six patterns from simple claude -p sequential pipelines and the NanoClaw REPL to the Infinite Agentic Loop, Continuous Claude PR loop, the De-Sloppify cleanup pass, and RFC-driven DAG orchestration. - Cross-Iteration Context: Uses SHARED_TASK_NOTES.md and filesystem state to bridge context between independent non-interactive invocations. - Quality Gates & Merge Coordination: Tiered pipelines (research, plan, implement, test, review) with separate context windows per stage and an agent-driven merge queue with eviction recovery. - Use Case: You have a written RFC for a large feature. Decompose it into a dependency DAG of work units, run each through a tiered quality pipeline in isolated worktrees, and land them via a merge queue that captures conflict context for re-runs. ## Quick Start Set up an autonomous Claude Code loop for my project by choosing the right pattern from the autonomous-loops skill and generating the pipeline script.