Which testing frameworks does this skill support?

The skill is framework-agnostic and adapts to your project's current environment, providing templates for popular tools like Jest, Vitest, Pytest, Playwright, and more.

Can it help increase my project's code coverage?

Yes, the workflow includes a dedicated verification step to identify untested paths and ensure both happy paths and edge cases are covered.

How does it map requirements to tests?

The skill follows a systematic mapping process where acceptance criteria from user stories are converted into specific test cases across unit, integration, and UI levels.

Does it handle mocking and test fixtures?

Absolutely. It provides specific patterns for creating reusable data fixtures and implementing consistent mocking to keep tests isolated and fast.

Testing Code & Quality Assurance

Name: Testing Code & Quality Assurance
Author: Activer007

byActiver007

安全与测试

Writes comprehensive automated tests across multiple layers to ensure software reliability and functional correctness.

关于

This skill provides a standardized workflow for implementing automated testing in software projects, covering unit, integration, component, and E2E tests. It guides Claude through determining test scope, mapping requirements to test cases, handling edge cases, and generating reusable test fixtures. By following established patterns and frameworks like Jest, Vitest, or Pytest, it helps maintain high code coverage and ensures that features align perfectly with technical specifications and user acceptance criteria.

主要功能

Comprehensive edge case, boundary condition, and error scenario validation
Requirement-to-test mapping to ensure 100% acceptance criteria coverage
Multi-layered test generation including Unit, Integration, Component, and E2E tests
Parallel agent strategies for rapid test implementation across large codebases
0 GitHub stars
Standardized mocking patterns and reusable test data fixtures

使用场景

Validating API contracts and integration points between distributed services
Increasing code coverage for legacy systems by identifying and filling testing gaps
Generating complete test suites for new features based on user stories and specs

关于

主要功能

Comprehensive edge case, boundary condition, and error scenario validation
Requirement-to-test mapping to ensure 100% acceptance criteria coverage
Multi-layered test generation including Unit, Integration, Component, and E2E tests
Parallel agent strategies for rapid test implementation across large codebases
0 GitHub stars
Standardized mocking patterns and reusable test data fixtures

使用场景

Validating API contracts and integration points between distributed services
Increasing code coverage for legacy systems by identifying and filling testing gaps
Generating complete test suites for new features based on user stories and specs