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Found 300 Skills
CUDA kernel development, debugging, and performance optimization for Claude Code. Use when writing, debugging, or optimizing CUDA code, GPU kernels, or parallel algorithms. Covers non-interactive profiling with nsys/ncu, debugging with cuda-gdb/compute-sanitizer, binary inspection with cuobjdump, and performance analysis workflows. Triggers on CUDA, GPU programming, kernel optimization, nsys, ncu, cuda-gdb, compute-sanitizer, PTX, GPU profiling, parallel performance.
Python performance optimization patterns using profiling, algorithmic improvements, and acceleration techniques. Use when optimizing slow Python code, reducing memory usage, or improving application throughput and latency.
1600+ lines of performance optimization mastery - profiling, rendering, memory, network, battery, APK size with production-ready code examples.
High-performance Rust optimization. Profiling, benchmarking, SIMD, memory optimization, and zero-copy techniques. Focuses on measurable improvements with evidence-based optimization.
Diagnose, improve, and prevent performance regressions in Expo-based React Native apps using release-build profiling, KPI budgets, and targeted fixes across startup, rendering, lists, images, memory, and networking.
Identify and debug performance regressions from code changes. Use comparison and profiling to locate what degraded performance and restore baseline metrics.
Identifies API latency hotspots and bottlenecks with profiling tools, slow endpoint detection, suspected causes, and fix roadmap. Use for "latency profiling", "performance bottlenecks", "slow APIs", or "backend performance".
Django-extensions management commands for project introspection, debugging, and development. Use when exploring URLs, models, settings, database schema, running scripts, or profiling performance. Triggers on questions about Django project structure, model fields, URL routes, or requests to run development servers.
Full Sentry SDK setup for Python. Use when asked to "add Sentry to Python", "install sentry-sdk", "setup Sentry in Python", or configure error monitoring, tracing, profiling, logging, metrics, crons, or AI monitoring for Python applications. Supports Django, Flask, FastAPI, Celery, Starlette, AIOHTTP, Tornado, and more.
Activate when a project needs competitive analysis, audience profiling, or positioning gaps before design begins.
Grafana Pyroscope continuous profiling platform. Covers instrumentation of Go/Java/Python/Ruby/Node.js/ .NET/Rust apps via SDKs or eBPF (Alloy), flame graph analysis, ProfileQL queries, server configuration and architecture, Grafana Cloud Profiles integration, and trace-profile linking (Span Profiles). Use when working with profiling data, instrumenting apps for Pyroscope, analyzing performance profiles, or deploying Pyroscope server.
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.