unit-test-generator

Unit Test Generator

Automatically generates comprehensive unit tests for your code, supporting multiple programming languages and testing frameworks.

What This Skill Does

This skill creates high-quality unit tests by:

• Analyzing function/method signatures and logic
• Generating test cases for happy paths
• Creating edge case tests
• Adding error condition tests
• Following language-specific best practices
• Using appropriate testing frameworks
• Including setup/teardown when needed

Instructions

1. Code Analysis

When asked to generate tests:

1. Identify target code:

   • Use Read to examine the source file
   • Parse function/class signatures
   • Understand parameters, return types, and dependencies

2. Detect language and framework:

   • Python: pytest, unittest
   • JavaScript/TypeScript: Jest, Mocha, Vitest
   • Go: testing package
   • Rust: built-in test framework
   • Java: JUnit

3. Analyze logic:

   • Identify all code paths
   • Find conditionals and branches
   • Locate error handling
   • Determine edge cases

2. Test Generation Strategy

Create tests covering:

Happy Path Tests:

• Normal input → expected output
• Valid use cases
• Common scenarios

Edge Cases:

• Empty inputs
• Boundary values (min, max)
• Special characters
• Large datasets
• Zero/null values

Error Conditions:

• Invalid inputs
• Type mismatches
• Missing required parameters
• Exception scenarios

Integration Points:

• Mock external dependencies
• Stub API calls
• Fake database interactions

3. Test Structure

Follow framework-specific conventions:

Python (pytest):

import pytest
from module import function_to_test

class TestFunctionName:
    def test_happy_path(self):
        # Arrange
        input_data = "valid input"

        # Act
        result = function_to_test(input_data)

        # Assert
        assert result == expected_value

    def test_edge_case_empty_input(self):
        with pytest.raises(ValueError):
            function_to_test("")