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This paper proposes scaffold-mediated post-training, a paradigm where procedural scaffolds co-evolve with LLM parameters through discovery, distillation, and dynamic recompilation. On FeatureBench, automatically discovered skills improve pass rate by 8.1pp, with a 27.7% pass rate after distillation.