patterns▌

Best practices for video and audio processing with FFmpeg.

Use when building or debugging Nuxt 4 apps with SSR, hybrid rendering, route rules, or page-level data fetching.

This meta-skill provides architectural patterns, best practices, and integration strategies for combining multiple 3D and animation libraries in web applications. It synthesizes knowledge from the threejs-webgl, gsap-scrolltrigger, react-three-fiber, motion-framer, and react-spring-physics skills into cohesive patterns for building complex, performant 3D web experiences.

Production-grade Django architecture patterns for scalable, maintainable applications. \n \n Covers project structure with split settings (base, development, production, test), custom managers and QuerySets, and service layer separation for business logic \n Includes Django REST Framework patterns: serializers with validation, ViewSets with custom actions, filtering, searching, and pagination \n Demonstrates ORM best practices: select_related and prefetch_related for N+1 prevention, bulk operati

Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.

Comprehensive testing strategies for Python using pytest, fixtures, mocking, and test-driven development. \n \n Covers unit, integration, functional, and performance testing with the AAA pattern (Arrange, Act, Assert) for test structure \n Includes 10 fundamental and advanced patterns: basic tests, fixtures with setup/teardown, parameterization, mocking, exception handling, async testing, monkeypatching, temporary files, custom fixtures, and property-based testing \n Provides test design princip

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Production-ready patterns for Apache Airflow DAGs, operators, sensors, testing, and deployment. \n \n Covers DAG design principles (idempotent, atomic, incremental, observable) with task dependency patterns for linear, fan-out, fan-in, and complex workflows \n Includes TaskFlow API decorators for cleaner code with automatic XCom passing, dynamic DAG generation from configs, and branching with conditional logic \n Provides sensor patterns for S3 files, external task dependencies, and custom senso

Idiomatic PyTorch patterns and best practices for building robust, efficient, and reproducible deep learning applications.

Comprehensive Ktor patterns for building robust, maintainable HTTP servers with Kotlin coroutines.