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Found 73 Skills
Concurrent operations with asyncio and Tokio, focusing on race condition prevention, resource safety, and performance
This skill provides async/await patterns and best practices for concurrent programming
Handle asynchronous operations safely using Futures and Streams.
Expert in asynchronous programming patterns across languages (Python asyncio, JavaScript/TypeScript promises, C# async/await, Rust futures). Use for concurrent programming, event loops, async patterns, error handling, backpressure, cancellation, and performance optimization in async systems.
Node.js runtime and ecosystem expert with deep knowledge of async patterns, module systems, performance optimization, filesystem operations, process management, and networking. Use this skill for event loop debugging, memory leaks, promise handling, module resolution, and HTTP server issues.
LP, MILP, QP — concepts, problem-text parsing, and formulation patterns (parameters, constraints, decisions, objective). Concepts only; no API.
Best practices for building WPF desktop applications with C# and .NET. Use when working on WPF projects, .NET desktop apps, XAML UI, MVVM architecture, system tray apps, or any C# project using Windows Presentation Foundation.
Complete guide for asyncio concurrency patterns including event loops, coroutines, tasks, futures, async context managers, and performance optimization
AWS SDK for Swift development patterns. Use when writing Swift code that uses AWS services via aws-sdk-swift package.
ALWAYS use when working with RxJS Observables, operators, and reactive patterns in Angular applications.
Master Rust async programming with Tokio, async traits, error handling, and concurrent patterns. Use when building async Rust applications, implementing concurrent systems, or debugging async code.
Manage software complexity through deep modules, information hiding, and strategic programming. Use when the user mentions "module design", "API too complex", "shallow class", "complexity budget", or "strategic vs tactical". Covers deep vs shallow modules, red flags for complexity, and comments as design documentation. For code quality, see clean-code. For boundaries, see clean-architecture.