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Operates autonomous agent loops, monitors progress, and intervenes safely when loops stall or degrade.

Quality gates, eval checkpoints, and recovery controls for continuous autonomous agent loops. Patterns for safe loop operation with stall detection and intervention hooks.

Use when the user asks to design multi-agent systems, create agent architectures, define agent communication patterns, or build autonomous agent workflows.

Autonomous agent loop architectures from simple to complex: sequential pipelines, infinite agentic loops with quality gates, continuous PR loops with CI gates, de-sloppify cleanup passes, and RFC-driven multi-agent DAG orchestration with merge queues.

Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation c...

Quality gates and stall detection for autonomous loops

Sequential to DAG orchestration architectures

Multi-agent autonomous dev: 41 agents, 7 swarms, zero human intervention.