# Performance Engineering

When validating system performance under load, identifying bottlenecks through...

- Repository: https://github.com/ancoleman/ai-design-components (526 stars)
- Category: Testing
- License: MIT
- Last updated: 2025-12-11
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add ancoleman/ai-design-components --skill performance-engineering -g -a claude-code -y`
Codex: `npx skills add ancoleman/ai-design-components --skill performance-engineering -g -a codex -y`
Cursor: `npx skills add ancoleman/ai-design-components --skill performance-engineering -g -a cursor -y`
Gemini CLI: `npx skills add ancoleman/ai-design-components --skill performance-engineering -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add ancoleman/ai-design-components`

## Description

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.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Performance Engineering

## Purpose

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 This Skill

**Common Triggers:**
- "Validate API can handle expected traffic"
- "Find maximum capacity and breaking points"
- "Identify why the application is slow"
- "Detect memory leaks or resource exhaustion"
- "Optimize Core Web Vitals for SEO"
- "Set up performance testing in CI/CD"
- "Reduce cloud infrastructure costs"

**Use Cases:**
- Pre-launch capacity planning and load validation
- Post-refactor performance regression testing
- Investigating slow response times or high latency
- Detecting memory leaks in long-running services
- Optimizing database query performance
- Validating auto-scaling configuration
- Establishing performance SLOs and budgets

## Performance Testing Types

### Load Testing
Validate system behavior under expected traffic levels.

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

### Stress Testing
Find system capacity limits and failure modes.

**When to use:** Capacity planning, understanding failure behavior, infrastructure sizing decisions.

### Soak Testing
Identify memory leaks, resource exhaustion, and degradation over time.

**When to use:** Detecting memory leaks, validating connection pool cleanup, testing long-running batch jobs.

### Spike Testing
Validate system response to sudden traffic spikes.

The rest: https://github.com/ancoleman/ai-design-components/blob/HEAD/skills/performance-engineering/SKILL.md