AgentTrace: Causal Graph Tracing for Root Cause Analysis in Deployed Multi-Agent Systems

As multi-agent AI systems are increasingly deployed in real-world settings, failures become harder to diagnose due to cascading effects, hidden dependencies, and long execution traces. AgentTrace is a lightweight causal tracing framework for post-hoc failure diagnosis in deployed multi-agent workflows. It reconstructs causal graphs from execution logs, traces backward from error manifestations, and ranks candidate root causes using interpretable structural and positional signals without requiring LLM inference at debugging time. Across a diverse benchmark of multi-agent failure scenarios designed to reflect common deployment patterns, AgentTrace localizes root causes with high accuracy and sub-second latency, significantly outperforming both heuristic and LLM-based baselines.