AGENTSCOPE System Targets LLM Agent Failure Diagnosis

DAIR.AI posted about an arXiv paper from Jiayi Bi at Tsinghua, Yanjie Gao and colleagues at Microsoft Research, and Tianyin Xu at UIUC. The work introduces AGENTSCOPE, a neuro-symbolic system that applies behavioral abstractions to long agent trajectories. Authors note that standard debugging tools fail on these traces and that passing full logs to an LLM judge is insufficient. The paper, titled Diagnosing with Insights: Structured Analysis of Agent Failures via Behavioral Abstractions, is available on arXiv under ID 2609.02371 and is also hosted on the DAIR.AI academy site.