AI RESEARCH
Insights Generator: Systematic Corpus-Level Trace Diagnostics for LLM Agents
arXiv CS.LG
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ArXi:2605.21347v1 Announce Type: cross Diagnosing failures in LLM agents remains largely manual. Practitioners inspect a small subset of execution traces, form ad-hoc hypotheses, and iterate. This process misses patterns that only emerge across trace populations and does not scale to production corpora where individual traces span tens of thousands of tokens. We formalize the problem of corpus-level trace diagnostics.