Mauricio Scheffer

Code skeletons (types, modules, signatures) beat prose design docs and behavioral specs in AWS’s new Skeleton Coding paper. - Code skeletons raised SDDBench mean test pass rate from 29% to 74% vs a task description alone. - With skeletons plus global invariants, a smaller model came within 5–8 percentage points of the larger model’s best results at 15–26× lower token cost. The best-performing specs combined modules, types, and signatures with natural-language contracts and global invariants. Richer .md architecture docs helped, but remained below the best code-like skeletons. Excessive contract detail hurt performance, especially for smaller models. Skeletons also reduced code erosion (a complexity-based proxy for maintainability) while behavioral specs increased it. Theory: structure changes which tests are sufficient. Interfaces expose intermediate states that end-to-end tests can miss. Limitations: the skeletons came from reference implementations. Costs exclude specification generation and evaluation. Unclear: how cheaply we can produce this structure upfront, and whether making the contracts mechanically checkable would improve results enough to justify the added cost. My bet: the best starting point for a coding agent isn’t more prose. It’s a model of the system and explicit constraints the implementation must satisfy. arxiv.org/abs/2610.38214