asking a model to verify and revise can damage answers that were already correct. Calibrated Answer Repair first estimates whether a draft will benefit from repair, then localizes the evidence and bounds the edit: across three financial-QA benchmarks and three open-weight models it recovers 14.6% of initially missed answer requirements while damaging only 2.1% of initially correct ones, at over 30% lower post-draft token cost than iterative revision.