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Found 221 Skills
Rust profiling skill for performance analysis. Use when generating flamegraphs from Rust binaries, measuring monomorphization bloat with cargo-llvm-lines, analysing binary size with cargo-bloat, microbenchmarking with Criterion, or interpreting inlined frames in profiles. Activates on queries about cargo flamegraph, cargo-bloat, cargo-llvm-lines, Criterion benchmarks, Rust performance profiling, or binary size analysis.
Swift 6.2 and SwiftUI performance optimization for iOS 26 clinic architecture codebases. Covers async/await concurrency patterns, Sendable/actor isolation, view/render performance, and animation performance while preserving modular MVVM-C boundaries across App, Feature, Domain, and Data layers. Use when profiling or optimizing Swift/SwiftUI behavior in clinic modules.
Rspack best practices for config, CLI workflow, type checking, CSS, bundle optimization, assets and profiling. Use when writing, reviewing, or troubleshooting Rspack projects.
Activate this skill when BenchmarkDotNet (BDN) is involved in the task — creating, running, configuring, or reviewing BDN benchmarks. Also activate when microbenchmarking .NET code would be useful and BenchmarkDotNet is the likely tool. Consider activating when answering a .NET performance question requires measurement and BenchmarkDotNet may be needed. Covers microbenchmark design, BDN configuration and project setup, how to run BDN microbenchmarks efficiently and effectively, and using BDN for side-by-side performance comparisons. Do NOT use for profiling/tracing .NET code (dotnet-trace, PerfView), production telemetry, or load/stress testing (Crank, k6).
Shared optimization guidance plus cuTile Python DSL-specific overlays. Use when: (1) selecting optimizations for a cuTile Python DSL kernel, (2) checking cuTile-specific implementation traps, (3) deciding whether a profiling finding belongs in shared knowledge or a cuTile overlay, (4) updating cuTile Python DSL optimization docs, (5) reviewing how a shared pattern maps to cuTile.
GPU kernel profiling workflow across supported kernel implementation languages. Provides commands for all 4 profiling modes (annotation, event, ncu, nsys), metric interpretation tables, bottleneck identification rules, and the output contract for returning compact results to the orchestrator. Use when: (1) profiling a kernel version, (2) interpreting profiling artifacts/reports, (3) comparing kernel versions, (4) identifying bottlenecks and optimization opportunities, (5) documenting performance in the development log.
Optimize MATLAB code for better performance through vectorization, memory management, and profiling. Use when user requests optimization, mentions slow code, performance issues, speed improvements, or asks to make code faster or more efficient.
Full Sentry SDK setup for Next.js. Use when asked to "add Sentry to Next.js", "install @sentry/nextjs", or configure error monitoring, tracing, session replay, logging, profiling, AI monitoring, or crons for Next.js applications. Supports Next.js 13+ with App Router and Pages Router.
Datadog Browser SDK — RUM, Logs, Session Replay, profiling, product analytics, and error tracking setup, configuration, and migration. Use when upgrading Browser SDK versions, setting up RUM or Logs, or troubleshooting browser-side Datadog instrumentation.
Performance profiling and bottleneck detection for Node.js, Python, and browser apps
Manages .NET project setup, build systems, and developer tooling including solution structure, MSBuild (authoring, tasks, Directory.Build), build optimization, performance patterns, profiling (dotnet-counters/trace/dump), Native AOT publishing, trimming, GC/memory tuning, CLI app architecture (System.CommandLine, Spectre.Console, Terminal.Gui), docs generation, tool management, version detection/upgrade, and solution navigation.
Python performance profiling with cProfile, tracemalloc, and line_profiler. Use for identifying bottlenecks and memory issues. USE WHEN: user mentions "Python profiling", "cProfile", "memory profiling", asks about "Python performance", "tracemalloc", "line_profiler", "py-spy", "Python optimization", "Python memory leak" DO NOT USE FOR: Java/Node.js profiling - use respective skills instead