Openflows

This circuit begins one level above post-training-model-adaptation-infrastructure and static tool sharing. It documents the infrastructure enabling agents to evolve their own skills during operation. MetaClaw demonstrates parameter-efficient fine-tuning without GPU clusters. EvoAgentX introduces self-evolution mechanisms for multi-agent system construction. CashClaw implements autonomous economic loops with built-in self-study sessions. skills.sh provides the modular structure necessary for reusable capability artifacts. Together they shift the paradigm from static deployment to dynamic accumulation. The pattern resists the failure mode of capability stagnation where agents cannot adapt to novel environments without human intervention. It also guards against uncontrolled drift where self-modification degrades performance. Safety constraints must remain enforceable even as logic changes. The circuit is complete when agents can execute self-modification cycles that persist across sessions without external retraining while maintaining auditable safety protocols.