mutation-testing
Evaluate test suite quality by introducing code mutations and verifying tests catch them. Use for mutation testing, test quality, mutant detection, Stryker, PITest, and test effectiveness analysis.
Discover documentation testing skills, compare source repositories and read the instructions for each workflow.
Evaluate test suite quality by introducing code mutations and verifying tests catch them. Use for mutation testing, test quality, mutant detection, Stryker, PITest, and test effectiveness analysis.
Detect unintended visual changes in UI by comparing screenshots across versions. Use for visual regression, screenshot diff, Percy, Chromatic, UI testing, and visual validation.
Implement synthetic monitoring and automated testing to simulate user behavior and detect issues before users. Use when creating end-to-end test scenarios, monitoring API flows, or validating user workflows.
Perform comprehensive code reviews with best practices, security checks, and constructive feedback. Use when reviewing pull requests, analyzing code quality, checking for security vulnerabilities, or providing...
Generate realistic, consistent test data using factories, fixtures, and fake data libraries. Use for test data, fixtures, mock data, faker, test builders, and seed data generation.
Design and implement scalable test automation frameworks with Page Object Model, fixtures, and reporting. Use for test framework, page object pattern, test architecture, test organization, and automation infras...
Comprehensive mobile app testing strategies for iOS and Android. Covers unit tests, UI tests, integration tests, performance testing, and test automation with Detox, Appium, and XCTest.
Run, validate, and analyze Cypress E2E tests for the InfluxData documentation site. Covers Hugo server management, test execution modes, and failure analysis.
This skill should be used when running .NET tests selectively with a build-first, test-targeted workflow. Use it for running tests with xUnit focus.
Add integration tests for type checker inference and checking functions
Minimal example Skill for testing skild installs.
Run mutation testing to validate test quality beyond code coverage. Use when assessing test effectiveness, finding weak tests, or validating test suite quality.
Suggest and apply fixes for flaky tests based on detected patterns. Use after flaky-detect identifies unreliable tests that need repair.
Identify flaky tests from CI history and test execution patterns. Use when debugging intermittent test failures, auditing test reliability, or improving CI stability.
Execute JavaScript/TypeScript tests with Vitest, supporting coverage, watch mode, and parallel execution. Use for JS/TS test automation.
Identify flaky tests from CI history and test execution patterns. Use when debugging intermittent test failures, auditing test reliability, or improving CI stability.
Suggest and apply fixes for flaky tests based on detected patterns. Use after flaky-detect identifies unreliable tests that need repair. Use when relevant to the task.
Auto-generate test data factories from schemas, types, or models. Use when creating test data infrastructure, setting up fixtures, or reducing test setup boilerplate.
Run mutation testing to validate test quality beyond code coverage. Use when assessing test effectiveness, finding weak tests, or validating test suite quality.
Execute Python tests with pytest, supporting fixtures, markers, coverage, and parallel execution. Use for Python test automation.
Verify bidirectional traceability from requirements to code to tests. Use when relevant to the task.
Detect orphaned tests, obsolete assertions, and test-code misalignment. Use for test suite maintenance, cleanup, and traceability validation.
Analyze test coverage, identify gaps, and recommend test improvements. Use when relevant to the task.
Auto-generate test data factories from schemas, types, or models. Use when creating test data infrastructure, setting up fixtures, or reducing test setup boilerplate.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.