A practical, tool-focused guide that helps agents assist users with performance analysis and optimization. It walks through measuring baseline performance, finding hot paths, applying targeted optimizations (algorithmic fixes, caching, vectorization, parallelism), and verifying gains with benchmarks and profiling tools. The content spans Python, JavaScript/Node, shell scripting, and system-level techniques so agents can recommend concrete commands and code changes.
Use this skill when a user reports slow code, high resource usage, or unclear bottlenecks; when asked how to profile an application; or when recommending language-specific profiling tools and concrete optimization patterns. Good for both quick fixes (I/O batching, caching) and deeper algorithmic work.
Agents with code execution and terminal capabilities (Codex/Copilot-style code assistants, Claude Code, Cursor, or any agent that can suggest shell commands) will be most useful. The guidance assumes ability to run profiling commands and inspect outputs.
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FFmpeg Guide
Comprehensive FFmpeg reference for encoding, converting, streaming, filtering, and analyzing audio/video — command examples, common patterns, and troubleshootin
FFmpeg
Commands and best-practices for using FFmpeg to transcode, convert, stream, and analyze audio/video — ideal for encoding, HLS/DASH, trimming, and batch processi
