PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading.
No tool requirements listed.
No connector requirements listed.
Flexible output.
Thread-safe data persistence in Swift using actors — in-memory cache with file-backed storage, eliminating data races by design.
Swift 6.2 Approachable Concurrency — single-threaded by default, @concurrent for explicit background offloading, isolated conformances for main actor types.
Protocol-based dependency injection for testable Swift code — mock file system, network, and external APIs using focused protocols and Swift Testing.
Use this skill when writing new features, fixing bugs, or refactoring code. Enforces test-driven development with 80%+ coverage including unit, integration, and E2E tests.
Interactive agent picker for composing and dispatching parallel teams