Systematic debugging for AI agents: Introducing the AgentRx framework

AgentRx has been launched as an open-source framework to identify the first critical failure step in AI agent trajectories. This release includes a dataset with 115 manually annotated failed trajectories, aiding the community in building more transparent and resilient systems. Modern AI agents are complex, performing numerous actions over extended periods, making error identification challenging. AgentRx shows significant improvements in failure localization by 23.6% and root-cause attribution by 22.9% compared to traditional methods.