What problem does it solve? Teams often ship applications without knowing how they behave under real traffic, leading to outages, SLA violations, and undetected bottlenecks. This Skill provides a systematic process for designing performance tests with defined SLAs, realistic scenarios, and bottleneck analysis instead of ad-hoc testing. ## Core Features & Use Cases - Test Scenario Design: Covers load, stress, spike, and endurance test types with ramp-up patterns, think time, and realistic user data. - Multi-Tool Support: Provides ready-to-adapt examples for k6 (JavaScript), JMeter (GUI/CLI/distributed), and Locust (Python) with thresholds and custom metrics. - Bottleneck Diagnosis & Capacity Planning: Maps symptoms like high response time or memory growth to root causes, plus autoscaling and capacity calculations. - Use Case: Before a product launch expecting 1000 concurrent users, generate a k6 script with p95 < 200ms thresholds, run it in CI, and produce a report identifying the database connection pool as the bottleneck. ## Quick Start Ask the AI to design a k6 load test for your API with a p95 under 200ms SLA at 1000 concurrent users, including bottleneck analysis and a capacity plan.