We describe Siraj’s Track B submission to AISA-ArabicFC. A QLoRA-tuned ALLaM-7B is followed by a separately trained argument repairer whose edits pass a type-restricted acceptance filter, then by one deterministic year rule. On the blind test set (1,125 rows) it scores 0.8245 ArgEM and 0.9101 Track B, 10th of 17 systems; the post-editing stage is worth about one example on test against four on development. Every rule that error inspection suggested was adjudicated on out-of-fold training predictions, scored with the task’s own published matcher, before it could touch development predictions; all five were rejected, one of them breaking 168 more rows than it fixed. Two development-time conclusions did not survive: the top three systems finished 5.5 to 5.7 ArgEM points ahead, so our error rate was not a task-level ceiling, and a later dataset revision lowers our development ArgEM from 0.850 to 0.8080 and neutralises our strongest rule. Post-editing rules fitted to gold conventions can inherit changes in those conventions.