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Found 10 Skills
Performance optimization expert covering profiling, benchmarking, memory allocation, SIMD, cache optimization, false sharing, lock contention, and NUMA-aware programming.
High-performance Rust optimization. Profiling, benchmarking, SIMD, memory optimization, and zero-copy techniques. Focuses on measurable improvements with evidence-based optimization.
Expert-level Rust performance optimization guidelines for build profiles, allocation, synchronization, async/await, and I/O. This skill should be used when writing, reviewing, or optimizing Rust code for performance. Triggers on tasks involving slow Rust code, large binary size, long compile times, LTO configuration, release profile tuning, allocation reduction, clone avoidance, lock contention, BufReader/BufWriter, flamegraph analysis, async runtime issues, Tokio performance, spawn_blocking, parking_lot vs std sync, or any Rust performance investigation.
Measure, profile, optimize, and regression-test Rust performance across latency, throughput, CPU, allocations, memory, binary size, and compile time using representative workloads, Criterion, iai-callgrind, cargo-flamegraph, samply, DHAT, heap or pprof tools, cargo-bloat, cargo-llvm-lines, and build timings. Use when users report slow Rust code, high memory or CPU, large binaries, noisy benchmarks, tail-latency regressions, or need performance budgets and evidence-backed optimization.
Advanced Rust patterns for ownership, traits, async, error handling, macros, type system tricks, unsafe, and performance. Use when tackling complex Rust problems — not basic syntax, but multi-concern tasks like designing cancellation-safe async services, choosing between trait objects and generics, building typestated APIs, structuring error hierarchies across crate boundaries, writing proc macros, or optimizing hot paths with zero-cost abstractions. Do not use for basic Rust syntax, simple CLI tools, or beginner ownership questions.
RTK CLI performance analysis and optimization. Startup time (<10ms), binary size (<5MB), regex compilation, memory usage. Use when adding dependencies, changing initialization, or suspecting regressions.
CRITICAL: Use for performance optimization. Triggers: performance, optimization, benchmark, profiling, flamegraph, criterion, slow, fast, allocation, cache, SIMD, make it faster, 性能优化, 基准测试
Rust performance optimization covering memory allocation, ownership efficiency, data structure selection, iterator patterns, async concurrency, algorithm complexity, compile-time optimization, and micro-optimizations. Use when optimizing Rust code performance, profiling hot paths, reducing allocations, or choosing optimal data structures. Complements the rust-refactor skill (idiomatic patterns and architecture). Does NOT cover code style, naming conventions, or project organization (see rust-refactor skill).
Rust performance optimization guidelines. This skill should be used when writing, reviewing, or refactoring Rust code to ensure optimal performance patterns. Triggers on tasks involving memory allocation, ownership, borrowing, iterators, async code, or performance optimization.
Clones, analyzes, plans, and migrates legacy codebases (C++, Fortran, Java, Python, C, Shell) from a GitHub URL or local directory to a modern, high-performance, deterministic, 100% Safe Rust architecture, tracking live telemetry across every task bucket, test failure/fix cycle, and Profile-Guided Optimization (PGO) stage, and producing a first-person AI storytelling report and interactive HTML infographic. Use when migrating a GitHub repository or local codebase to Rust, porting legacy C++, Fortran, Python, or Java workloads to memory-safe Rust, designing Struct-of-Arrays (SoA) or SIMD Rust architectures, or optimizing Rust ports with LLVM PGO. Don't use for unrelated non-Rust refactoring or single-line syntax questions.