Announced Breaks Separate Conformal Reliability from Frequency Calibration

Online forecasters sometimes know a regime boundary before any post-boundary labels arrive. Standard adaptive conformal methods still react through later coverage errors, so they can pay a detection-delay cost even when the boundary is public. We study conformal prediction with an announced partition of the stream and separate two post-break audits. The reset empirical quantile in segmented split-CP attains the minimax per-time probability-gap rate $\Theta(M^{-1/2})$ after $M$ post-reset scores, with a matching Le Cam lower bound. A pure bounded constant-step announced-break ACI recursion attains an $O(M^{-1})$ time-averaged empirical-frequency gap by telescoping, but this is a realized-frequency statement, not a guarantee for the next interval. The practical AB-ACI implementation used in experiments adds burn-in and projection, so its rate claim includes explicit correction terms and is not unconditional. Synthetic experiments recover both slopes and show short-window gains when the break is large. Two real-data applications are null under leakage-free protocols. ERCOT RTC+B gives 0.863 post-reform coverage for AB-ACI versus 0.880 for ACI, and FOMC yield breaks give 0.892 versus 0.900. The message is diagnostic: use the reset empirical quantile for per-prediction reliability, use AB-ACI only for long-run frequency audits, and expect gains only when the realized score shift is large enough to make detection delay costly.