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AutoSaddler is a Microsoft tool that automatically optimizes LLM-agent harnesses by diagnosing execution traces and applying structured updates to prompts, tools, and middleware, demonstrating significant benchmark improvements.
This paper introduces EvoSOP, a framework that enables LLM agents to synthesize atomic actions into reusable Standard Operating Procedures (SOPs) and iteratively optimize their toolset, significantly improving task success rates and reducing interaction rounds.
BohuTANG found through quantitative analysis that adding dedicated grep and glob functions to the pi tool reduces the detours of LLM-generated bash and improves efficiency.