Which programming languages does this skill support?

It provides specific patterns for Python (pytest), TypeScript (Jest/Vitest), and Ruby (RSpec), but the core testing principles are applicable to any modern programming language.

How does it help with test maintenance?

By enforcing 'behavioral testing' over 'implementation testing,' it ensures your tests remain valid even when you refactor the internal logic of your functions.

Does it handle complex dependencies and mocking?

Absolutely. It includes specific patterns for mocks, stubs, spies, and fakes to ensure your unit tests remain isolated and fast.

Does it support API testing?

Yes, it includes dedicated patterns for integration and API testing, focusing on request/response validation and data persistence.

Can this skill help with existing legacy code?

Yes, it can analyze existing modules to identify public interfaces, behaviors, and edge cases, then generate a corresponding test suite to improve coverage.

Test Patterns

Name: Test Patterns
Author: jayteealao

byjayteealao

보안 및 테스팅

Generates robust, production-grade test suites using industry-standard patterns and best practices across multiple languages and frameworks.

소개

The Test Patterns skill empowers developers to architect comprehensive test suites by applying proven methodologies like Arrange-Act-Assert (AAA) and behavioral testing. It provides standardized templates for unit and integration tests, automates the creation of test data factories, and ensures language-specific best practices for frameworks like pytest, Jest, Vitest, and RSpec. Whether you are improving legacy coverage or building a suite from scratch, this skill helps maintain resilient, independent, and descriptive tests that simplify long-term maintenance and improve code reliability.

주요 기능

Automated Arrange-Act-Assert (AAA) test structuring
Smart test data factory and fixture generation
Multi-framework support for Pytest, Vitest, Jest, and RSpec
0 GitHub stars
Integration and API testing pattern implementation
Edge case identification and coverage analysis

사용 사례

Generating comprehensive unit tests for new business logic
Refactoring brittle implementation-focused tests into behavioral tests
Setting up complex integration tests with mocked external dependencies

소개

주요 기능

Automated Arrange-Act-Assert (AAA) test structuring
Smart test data factory and fixture generation
Multi-framework support for Pytest, Vitest, Jest, and RSpec
0 GitHub stars
Integration and API testing pattern implementation
Edge case identification and coverage analysis

사용 사례

Generating comprehensive unit tests for new business logic
Refactoring brittle implementation-focused tests into behavioral tests
Setting up complex integration tests with mocked external dependencies