·performance-engineering
>_

performance-engineering

ancoleman/ai-design-components

When validating system performance under load, identifying bottlenecks through profiling, or optimizing application responsiveness. Covers load testing (k6, Locust), profiling (CPU, memory, I/O), and optimization strategies (caching, query optimization, Core Web Vitals). Use for capacity planning, regression detection, and establishing performance SLOs.

10Installs·0Trend·@ancoleman

Installation

$npx skills add https://github.com/ancoleman/ai-design-components --skill performance-engineering

SKILL.md

Performance engineering encompasses load testing, profiling, and optimization to deliver reliable, scalable systems. This skill provides frameworks for choosing the right performance testing approach (load, stress, soak, spike), profiling techniques to identify bottlenecks (CPU, memory, I/O), and optimization strategies for backend APIs, databases, and frontend applications.

Use this skill to validate system capacity before launch, detect performance regressions in CI/CD pipelines, identify and resolve bottlenecks through profiling, and optimize application responsiveness across the stack.

When to use: Pre-launch capacity planning, regression testing after refactors, validating auto-scaling.

When validating system performance under load, identifying bottlenecks through profiling, or optimizing application responsiveness. Covers load testing (k6, Locust), profiling (CPU, memory, I/O), and optimization strategies (caching, query optimization, Core Web Vitals). Use for capacity planning, regression detection, and establishing performance SLOs. Source: ancoleman/ai-design-components.

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Facts (cite-ready)

Stable fields and commands for AI/search citations.

Install command
npx skills add https://github.com/ancoleman/ai-design-components --skill performance-engineering
Category
>_Productivity
Verified
First Seen
2026-02-01
Updated
2026-02-18

Quick answers

What is performance-engineering?

When validating system performance under load, identifying bottlenecks through profiling, or optimizing application responsiveness. Covers load testing (k6, Locust), profiling (CPU, memory, I/O), and optimization strategies (caching, query optimization, Core Web Vitals). Use for capacity planning, regression detection, and establishing performance SLOs. Source: ancoleman/ai-design-components.

How do I install performance-engineering?

Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/ancoleman/ai-design-components --skill performance-engineering Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor

Where is the source repository?

https://github.com/ancoleman/ai-design-components