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From General Agents to RCA Experts: A Self-Evolving Harness for Root Cause Analysis

arXiv cs.SE LLM Agents Haiyu Huang, Jiewei Lyu, Zhihan Jiang, Jinyang Liu, Xiao He, Tieying Zhang, Wu Xiang, Michael R. Lyu 2026-08-26
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TL;DR - OpsHarness is a self-evolving harness that adapts general-purpose LLM agents for root cause analysis by converting prior diagnostic experience into reusable, system-specific expertise. It reports 59.0% top-1 accuracy across public benchmarks and an industrial deployment, outperforming both an unmodified general agent and specialized RCA baselines.

  • The study finds modern general agents often outperform purpose-built RCA agents, but their external adaptation harness remains a key production bottleneck.
  • OpsHarness combines layered operational knowledge and an “idea-card” tool library with workflows for setup, diagnosis, evolution, and verification.
  • It learns by contrasting successful and failed diagnostic trajectories, extracting atomic update proposals, and applying dual-gate verification to limit overfitting and regressions.
  • Its 59.0% top-1 accuracy represents a 63.4% improvement over a bare general agent and a 4.02Ă— improvement over baseline RCA agents.

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