AVERT: A Tool-Verified Agent with Responsibility-Routed Rule Evolution for Telecom Root Cause Analysis

Telecom root cause analysis (RCA) is critical for service restoration and repair planning during multi-site outages. LLM agents struggle because evidence is scattered across long alarm streams and topology graphs, candidate causes may lack evidential support, and free-form reasoning is difficult to verify. To address these challenges, we present AVERT, an RCA agent that follows an iterative hypothesis–diagnosis–verification workflow. Given the incident evidence, AVERT first forms an initial root-cause hypothesis. The Rule-Constraint Layer then structures the diagnosis into three stages: candidate enumeration, causal and topological constraint checking, and verdict selection, producing a provisional diagnosis. The Verification-Feedback Layer tests this diagnosis against service-path impact and feeds blocked paths, surviving sites, and counterexamples back to revise the hypothesis and rerun the rule stages. To keep the rule layer adaptive as incident patterns evolve, we introduce offline Responsibility-Routed Rule Evolution, which uses evaluator feedback and execution traces to identify the responsible stage and update only the corresponding rules. We evaluate AVERT on TelcoOutageBench, comprising 131 real-world telecom incidents. Compared with frontier model baselines, AVERT improves the mean RCA Score by 2.71–13.81 percentage points across all eight backbones, including Claude Opus 4.6, GPT-5.4, and GLM-5.1.