grafana-k6-skills

Use when interpreting k6 test output, analyzing performance metrics, identifying bottlenecks, tuning thresholds, or optimizing k6 test scripts. Use when the user has k6 test results and needs to understand response times, error rates, percentiles (p95, p99), or performance degradation patterns.

Use when designing k6 load profiles, choosing executors, configuring VU patterns, setting thresholds, or planning test scenarios. Use when the user asks about stress test, spike test, soak test, breakpoint test, load model, executor selection, or pass/fail criteria.

Use when creating k6 load test scripts for HTTP REST APIs, gRPC services, or WebSocket connections. Use when the user mentions load testing, performance testing, stress testing, API testing, or k6 script generation for protocol-level endpoints.

Use when creating k6 browser-based performance tests, testing frontend performance, measuring Web Vitals (LCP, FCP, CLS, INP, TTFB), or automating browser interactions for load testing. Use when the user mentions browser testing, page load testing, E2E performance, or Chromium-based testing with k6.

Use when analyzing an existing API codebase to auto-generate k6 load test scripts. Use when the user wants to create k6 tests from source code, route definitions, controllers, or middleware in frameworks like Express, NestJS, Spring Boot, FastAPI, or Django.

Use when generating k6 load test scripts from OpenAPI specification files (YAML or JSON). Use when the user has an OpenAPI spec, API specification, or wants to create k6 tests from API documentation defined in OpenAPI 3.0 or 3.1 format.

Use when setting up k6 in CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins), configuring distributed testing with k6-operator on Kubernetes, or managing k6 extensions (xk6). Use when the user wants to automate performance tests in a pipeline or run distributed load tests.

Use when creating chaos engineering or resilience tests with k6 and xk6-disruptor. Use when the user wants to inject faults (pod failures, network delays, HTTP errors) into Kubernetes services during load tests, validate circuit breakers, or test system recovery behavior.