Lightweight TF-IDF detectors outperform LLM judges by 4–8x at catching agents that falsely claim task completion, with 3,300x lower latency.
Summary
Agent silent failures—tasks reported done but actually incomplete—corrupt production monitoring. Relying on LLM judges to catch this costs you latency and misses failures; domain-calibrated statistical detectors are the practical alternative.
Why it matters
Agent silent failures—tasks reported done but actually incomplete—corrupt production monitoring. Relying on LLM judges to catch this costs you latency and misses failures; domain-calibrated statistical detectors are the practical alternative.
Implementation verdict
Replace LLM-based agent completion verification with task-specific TF-IDF triage. Requires baseline labeling on your domain (tau2-bench: AUROC 0.83; AppWorld: 0.95 achieved). Worth deploying now as monitoring layer—no latency penalty, proven higher recall.
Sources
Dev Signal
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