What Should Survive a Failed Plan? Counterfactual Reuse with World Models

World models can reject a plan before execution, but a failed prediction does not say which earlier decisions the next search should keep. We formulate this problem as counterfactual plan reuse: nominate a single action edit, decide whether to retain the prefix it defines, and search for a completion under a shared prediction budget. ROOTCAUSE scores every candidate edit by its effect on the same diagnosed failure, so a repair can be placed before the first visible symptom, then decides with paired world-model predictions whether the resulting branch deserves the search it would concentrate. Its central quantity is the value of one more check against the candidates that check displaces, so confirmation depth follows the budget instead of being fixed in advance. On four manipulation families with a frozen World Action Planner, ROOTCAUSE raises matched-budget success from 80.7% for the strongest baseline to 84.6%, with the largest gains on long-horizon tasks and a margin over fixed-depth confirmation that grows from 0.3 to 4.6 points as the budget quadruples. Held-out audits of action-response fidelity and calibration transfer locate the regime in which retaining actions pays and where it stops.