When Agents Fail to Act: A Diagnostic Framework for Tool Invocation Reliability in Multi-Agent LLM Systems

This research introduces a comprehensive diagnostic framework that utilizes big data analytics to evaluate the procedural reliability of intelligent agent systems. It addresses critical needs for deployments in privacy-sensitive environments, particularly for small and medium-sized enterprises (SMEs), and includes a 12-category error taxonomy.