AgentDebugX: Open-Source Toolkit for Debugging LLM Agent Failures
AgentDebugX is an open-source framework that structures LLM agent debugging into a closed loop of Detect, Attribute, Recover, and Rerun. Its core component, DeepDebug, achieves 28.8% exact attribution accuracy on the Who and When benchmark and repairs 13 of 73 failed tasks on GAIA in a single rerun, outperforming several baselines. The toolkit is available as a Python library, CLI, web console, and installable agentic skill.
Why it matters: AgentDebugX provides systematic root-cause diagnosis and recovery for LLM agents, addressing a key challenge in improving agent reliability and robustness.
Full story at: arXiv AI/ML ↗