This helps you design and run performance tests to measure response times, throughput, and resource usage under load. It covers k6 for API load testing, JMeter, pytest-benchmark for Python, JMH for Java, and database query analysis. You get working examples with realistic test stages, custom metrics, and threshold configurations. The best practices are solid: use percentiles over averages, test with realistic data volumes, and always warm up before measuring. It's opinionated about testing in production-like environments and catching N+1 queries early. Good for validating SLAs, finding bottlenecks before they hit production, or comparing performance before and after optimizations.
npx -y skills add aj-geddes/useful-ai-prompts --skill performance-testing --agent claude-codeInstalls into .claude/skills of the current project.
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wshobson/agents
dbt-labs/dbt-agent-skills
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