Fine-tuning on OpenHands trajectories causes performance degradation in other CLI scaffolds

Models fine-tuned on OpenHands trajectory datasets show significant performance loss when deployed in non-training scaffolds. This divergence is caused by the model internalizing scaffold-specific planning structures rather than general reasoning, specifically regarding explicit and implicit planning conventions.