Browse QA Skills

Testing monitoring and alerting configurations including threshold validation, alert routing, escalation policies, and false-positive rate monitoring.

Validating A/B test implementations including traffic splitting accuracy, statistical significance calculation, metric tracking, and experiment cleanup.

Anonymizing production data for testing while maintaining referential integrity, data distributions, and edge case representation.

Instrument LLM apps with Langfuse tracing, then use traces, scores, and datasets to test in production, run evaluations on real traffic, catch regressions, and close the loop from incident to golden dataset.

Optimizing test coverage beyond line coverage including branch coverage, mutation score, path coverage, and identifying meaningful coverage gaps.

Python-based load testing with Locust for writing user behavior scripts, distributed testing, real-time web UI monitoring, and custom load shapes.

Testing LLM-powered features including output quality validation, hallucination detection, token usage monitoring, and prompt regression testing.

Expert-level CI/CD pipeline skill for test automation. Covers GitHub Actions, Jenkins, GitLab CI, Azure DevOps, parallel execution, matrix strategies, caching, artifact management, and deployment gates.

Cloud-based cross-browser and cross-device testing with BrowserStack including Automate, App Automate, Percy visual testing, Observability, and integration with Playwright, Selenium, and CI/CD pipelines.

Managing test environments including provisioning, configuration, data seeding, isolation, cleanup, and environment-as-code patterns.

Testing Docker containers and images including Dockerfile linting, container structure tests, security scanning, and multi-stage build validation.

Designing scalable test architectures including test pyramid, diamond, trophy, and honeycomb patterns with framework-agnostic implementation.

Test fixture design patterns including builders, factories, object mothers, and fixture management for maintainable test data setup.

Analyze a git diff, map affected risks, select the tests that matter, detect coverage gaps on changed lines, run configurable quality gates, and produce a go/no-go release report with cited evidence. Recommends only; never merges or deploys.

Perform language and framework specific security best-practice reviews, vulnerability detection, and secure-by-default coding guidance for Python, JavaScript/TypeScript, and Go applications.

API simulation and service virtualization with WireMock for HTTP stubbing, request matching, stateful behavior, and fault injection testing.

Writing and testing YARA rules for malware detection, threat hunting, and file classification with rule validation and false-positive rate testing.

Advanced Allure test reporting with custom categories, environment info, test history trends, flaky test detection, and CI/CD dashboard integration.

Expert-level Lettuce BDD testing skill for Python applications. Covers Gherkin feature files, step definitions, terrain hooks, Selenium integration, data-driven scenarios, and migration guidance to Behave for modern projects.