How does this skill improve test execution speed?

By implementing fixture scoping (module and session) and strict isolation, it ensures expensive setups are shared where appropriate while keeping tests deterministic and fast.

Does it support mock management?

Yes, it includes patterns for creating mock repositories, service isolation, and cleaning up mocks using afterEach hooks to prevent state leakage between tests.

Can I use this for complex parameterization?

Absolutely. It includes templates for indirect parametrization and combinatorial testing to run comprehensive access matrices with minimal boilerplate.

What testing frameworks does this skill support?

It provides optimized patterns and best practices for Vitest, Jest, and pytest, covering both modern TypeScript/JavaScript and Python ecosystems.

What is the recommended coverage target for business logic?

This skill recommends a 90%+ coverage target for business logic and 100% coverage for critical paths and new features to ensure production stability.

Unit Testing Patterns

Name: Unit Testing Patterns
Author: yonatangross

byyonatangross

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Security & Testing

Implements robust unit testing patterns and best practices for TypeScript and Python using the AAA pattern and optimized fixtures.

About

The Unit Testing skill provides a comprehensive toolkit for building fast, deterministic tests that isolate business logic from external dependencies. It equips Claude with industry-standard patterns like Arrange-Act-Assert (AAA), advanced fixture scoping for pytest, and parameterized testing strategies for Vitest. Whether you are aiming for high coverage targets on critical paths or setting up fresh test suites, this skill ensures your codebase remains stable and maintainable through high-quality test generation and implementation guidance based on 2026 best practices.

Key Features

Provides advanced pytest fixture scoping (function, module, session) for optimized performance.
Ensures test isolation using fresh instances and proper mock cleanup strategies.
Supports parameterized and combinatorial testing to efficiently cover multiple edge cases.
29 GitHub stars
Defines clear coverage targets for business logic, critical paths, and utilities.
Standardizes tests using the Arrange-Act-Assert (AAA) pattern for maximum readability.

Use Cases

Generating isolated unit tests for complex business logic in FastAPI or React applications.
Implementing multi-scenario validation using indirect parametrization and stacked decorators.
Refactoring legacy test suites to follow modern deterministic mocking patterns.

About

Key Features

Provides advanced pytest fixture scoping (function, module, session) for optimized performance.
Ensures test isolation using fresh instances and proper mock cleanup strategies.
Supports parameterized and combinatorial testing to efficiently cover multiple edge cases.
29 GitHub stars
Defines clear coverage targets for business logic, critical paths, and utilities.
Standardizes tests using the Arrange-Act-Assert (AAA) pattern for maximum readability.

Use Cases

Generating isolated unit tests for complex business logic in FastAPI or React applications.
Implementing multi-scenario validation using indirect parametrization and stacked decorators.
Refactoring legacy test suites to follow modern deterministic mocking patterns.