Generate unit and integration tests with deep assertions across JavaScript, Python, and Go.
npx skills add https://github.com/mbwsims/claude-universe --skill test-mbwsims
Please help me install this Agent Skill. Skill: test Source: https://github.com/mbwsims/claude-universe/tree/main/skills/test Command: npx skills add https://github.com/mbwsims/claude-universe --skill test-mbwsims
This Skill tackles the issue of superficial tests that only cover happy paths, missing real bugs and edge cases that cause production failures.
Generate thorough tests for the login function in auth.js, including error cases for invalid credentials.
High-intent search queries and answers about installing and using this skill.
To generate bug-hunting unit tests, you need systematic input space analysis and deep assertions that verify exact values, error types, and side effects rather than just checking for existence. This ensures tests catch real bugs and edge cases.
Yes, automated test generation can apply to integration testing of functions, modules, or files across languages like JavaScript, Python, and Go. It requires framework detection and code contract extraction to produce reliable, executable tests.
The best way to write deep test assertions is to extract code contracts and verify exact values, specific error types, and side effects during execution. This goes beyond superficial testing to ensure robustness against invalid inputs and duplicates.
Automated test generation works with existing test frameworks by automatically detecting the framework you use. It then maps input spaces and generates executable tests that run through your framework for reliable outcomes.
Your tests miss production failures because they likely only cover happy paths and superficial assertions. Without systematic input space analysis to identify edge cases like invalid emails or duplicate users, tests fail to catch real bugs.
To test a user registration function, generate tests covering valid inputs, invalid emails, duplicate users, and database saves. This systematic approach verifies exact values and side effects to ensure the function handles errors robustly.
jlifengGenerate structured code-spec updates with signatures, contracts, and validation matrices.
jaisonerickReproduce QA-reported failures with failing tests and apply minimal code fixes.
liauw-mediaConfigure pre-commit hooks for JavaScript/TypeScript, Python, and PHP projects.
CENKSSSIntroduce code mutations and measure kill rate with Stryker and Jest.
