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Found 236 Skills
How WAL mechanics, checkpointing, concurrency rules, recovery work in tursodb
Checklists and anti-patterns for reviewing Go code. Covers API design, error handling, concurrency, interfaces, safety, performance, naming, testing, functional options, logging, and deterministic simulation testing.
Review Java code for language and runtime conventions: concurrency, exceptions, try-with-resources, API versioning, collections and Streams, NIO, and testability. Language-only atomic skill; output is a findings list.
Comprehensive Java development best practices covering SOLID principles, DRY, Clean Code, Java-specific patterns (Optional, immutability, streams, lambdas), exception handling, collections, concurrency, testing with JUnit 5 and Mockito, code organization, performance optimization, and common anti-patterns. Essential reference for uncle-duke-java agent during code reviews and architecture guidance.
Systematic code review for Java with null safety, exception handling, concurrency, and performance checks. Use when user says "review code", "check this PR", "code review", or before merging changes.
Parse SGLang/vLLM startup logs to explain GPU memory use and request capacity. Use for KV cache budget, mem-fraction-static comparisons, OOM triage, and max-concurrency estimates.
Rust event-driven system programming best practices for async runtimes, channels, sockets, terminals, and concurrency. This skill should be used when writing, reviewing, or refactoring Rust applications with async I/O, multi-threading, terminal interfaces, or network communication. Triggers on tasks involving tokio, async/await, channels, sockets, TTY handling, signals, and streaming I/O.
Use when needing synchronous actor access in tests, legacy delegate callbacks, or performance-critical code. Covers MainActor.assumeIsolated, @preconcurrency protocol conformances, crash behavior, Task vs assumeIsolated.
Analyze code for performance issues and suggest optimizations. Use when users ask to "optimize this code", "find performance issues", "improve performance", "check for memory leaks", "review code efficiency", or want to identify bottlenecks, algorithmic improvements, caching opportunities, or concurrency problems.
Python patterns for CLI tools, async concurrency, and backend services. Use when working with Python code, building CLI apps, FastAPI services, async with asyncio, background jobs, or configuring uv, ruff, ty, pytest, or pyproject.toml.
Performance and scalability analysis specialist. Identifies algorithmic inefficiencies, N+1 queries, memory leaks, and concurrency issues. Use when reviewing loops, database queries, file I/O, or high-concurrency code.
Use when needing thread-safe primitives for performance-critical code. Covers Mutex (iOS 18+), OSAllocatedUnfairLock (iOS 16+), Atomic types, when to use locks vs actors, deadlock prevention with Swift Concurrency.