From Atomic Actions to Standard Operating Procedures: Iterative Tool Optimization for Self-Evolving LLM Agents

EvoSOP: LLM agents self-evolve by synthesizing atomic actions into reusable Standard Operating Procedures

Researchers propose EvoSOP, a framework enabling LLM agents to extract reusable Standard Operating Procedures (SOPs) from execution trajectories, effectively converting sequences of atomic tool calls into higher-order callable tools. The framework iteratively optimizes the agent's toolset through a lifecycle of construction, merging, evaluation, and pruning. Experiments show EvoSOP improves task success rates and reduces interaction rounds compared to static-toolset baselines, offering a scalable path toward self-evolving agents.