Estimating and Communicating Correctness in Agent Handoffs

A correctness estimate from three sender responses enables lower-loss agent handoffs through a simple cost-aware decision rule. We fit a compact predictor to three token-probability features and communicate its correctness probability with an explanation. The sampling budget, predictor, and decision policy are configurable. The receiver reads only the note and selects a fault or requests specialist investigation. The estimator has useful ranking and lower probability error than raw self-reported confidence. On 125 incidents, its message reduces wrong diagnoses by 5.2 percentage points and increases escalation by 4.8 points relative to no warning. When escalation costs half as much as a wrong diagnosis, a gate on the same estimate lowers loss from 0.408 to 0.360 relative to the recorded probability-message decisions. Two simpler numerical messages do not reproduce this effect. Adding disagreement detail, even a complete twenty-answer tally, has no detectable effect under the original instructions. A separate comparison removes the explicit diagnosis while retaining evidence and votes. Fewer wrong diagnoses and more escalations recur on held-out incidents and with a second sender, with a clear effect in one of three receiver families. We evaluate both changes against the extra cost of escalation.