This paper develops a new method for optimizing skills for Large Language Model (LLM) agents, using a graph-structured representation that provides clearer workflow-level guidance and enables more effective exploration of the skill space. Practitioners might care because this approach can improve the performance of LLM agents in various tasks.
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