Objective. To facilitate implementation of plan-of-the-day (POTD) selection for treating locally advanced cervical cancer (LACC), we developed a POTD assessment tool for CBCT-guided radiotherapy (RT). A female pelvis segmentation model (U-Seg3) is combined with a novel quantitative standard operating procedure (qSOP) to identify optimal and acceptable plans. Approach. The planning CT[i], corresponding structure set[ii], and manually contoured CBCTs[iii] (n = 226) from 39 LACC patients treated with POTD (n = 11) or non-adaptive RT (n = 28) were used to develop U-Seg3, an algorithm incorporating deep-learning and deformable image registration techniques to segment the low-risk clinical target volume (LR-CTV), high-risk CTV (HR-CTV), bladder, rectum, and bowel bag. A single-channel input model (iii only, U-Seg1) was also developed. Contoured CBCTs from the POTD patients were (a) reserved for U-Seg3 validation/testing, (b) audited to determine optimal and acceptable plans, and (c) used to empirically derive a qSOP that maximised classification accuracy. Main results. The median (interquartile range) dice similarity coefficient (DSC) between manual and U-Seg3 contours was 0.83 [0.80], 0.78 [0.13], 0.94 [0.05], 0.86 [0.09], and 0.90 [0.05] for the LR-CTV, HR-CTV, bladder, rectum, and bowel. These were significantly higher than U-Seg1 in all structures but bladder. The qSOP classified plans as acceptable if they met target coverage thresholds (LR-CTV