Total 44,144 skills, Testing & QA has 1628 skills
Showing 12 of 1628 skills
Test smart contracts comprehensively using Hardhat and Foundry with unit tests, integration tests, and mainnet forking. Use when testing Solidity contracts, setting up blockchain test suites, or validating DeFi protocols.
Unit tests for external REST APIs using WireMock to mock HTTP endpoints. Use when testing service integrations with external APIs.
Эксперт Detox тестирования. Используй для React Native E2E tests и mobile automation.
pytest-django testing patterns, Factory Boy, fixtures, and TDD workflow. Use when writing tests, creating test factories, or following TDD red-green-refactor cycle.
Complete browser automation with Playwright. Auto-detects dev servers, writes clean test scripts to /tmp. Test pages, fill forms, take screenshots, check responsive design, validate UX, test login flows, check links, automate any browser task. Use when user wants to test websites, automate browser interactions, validate web functionality, or perform any browser-based testing.
Provides guidance for property-based testing across multiple languages and smart contracts. Use when writing tests, reviewing code with serialization/validation/parsing patterns, designing features, or when property-based testing would provide stronger coverage than example-based tests.
Worker that runs existing tests to catch regressions. Auto-detects framework, reports pass/fail. No status changes or task creation.
Techniques for patching code to overcome fuzzing obstacles. Use when checksums, global state, or other barriers block fuzzer progress.
Unit tests for scheduled and async tasks using @Scheduled and @Async. Mock task execution and timing. Use when validating asynchronous operations and scheduling behavior.
Coverage analysis measures code exercised during fuzzing. Use when assessing harness effectiveness or identifying fuzzing blockers.
Jest testing best practices for JavaScript and TypeScript applications, covering test structure, mocking, and assertion patterns.
Techniques for writing effective fuzzing harnesses across languages. Use when creating new fuzz targets or improving existing harness code.