The library project, on the other hand, contains the actual core gameplay logic. In the inventory service's case, this includes the C# classes that model the request and response for every API operation as well as the underlying logic for handling the countless inventory related systems such as crafting, quests, loot, etc. As a separate project, the library can be imported in other services when we need to reuse that logic without pulling in any of the web project's code.
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GlyphNet’s own results support this: their best CNN (VGG16 fine-tuned on rendered glyphs) achieved 63-67% accuracy on domain-level binary classification. Learned features do not dramatically outperform structural similarity for glyph comparison, and they introduce model versioning concerns and training corpus dependencies. For a dataset intended to feed into security policy, determinism and auditability matter more than marginal accuracy gains.