---

name: test-generator description: Activates when generating unit tests, integration tests, or test cases for code version: 1.0.0

Test Generator

Overview

This skill helps generate comprehensive test cases for various types of code. It creates unit tests, integration tests, and edge case tests that follow best practices and testing frameworks.

Instructions

When generating tests, follow these steps:

1. Analyze the Code: Understand what the code does, its inputs, outputs, and dependencies
2. Identify Test Cases: Determine happy path, edge cases, and error scenarios
3. Choose Framework: Use the appropriate testing framework for the language
4. Write Tests: Create clear, maintainable test cases with descriptive names
5. Add Assertions: Include proper assertions and expected outcomes
6. Document: Add comments for complex test scenarios

Examples

Example 1: Python Function Test

Input:

Copydef calculate_discount(price, discount_percent):
    if discount_percent < 0 or discount_percent > 100:
        raise ValueError("Discount must be between 0 and 100")
    return price * (1 - discount_percent / 100)

Output:

Copyimport pytest

def test_calculate_discount_valid():
    """Test discount calculation with valid inputs."""
    assert calculate_discount(100, 20) == 80.0
    assert calculate_discount(50, 10) == 45.0

def test_calculate_discount_zero():
    """Test with zero discount."""
    assert calculate_discount(100, 0) == 100.0

def test_calculate_discount_full():
    """Test with 100% discount."""
    assert calculate_discount(100, 100) == 0.0

def test_calculate_discount_negative():
    """Test that negative discount raises ValueError."""
    with pytest.raises(ValueError, match="Discount must be between 0 and 100"):
        calculate_discount(100, -10)

def test_calculate_discount_over_hundred():
    """Test that discount over 100 raises ValueError."""
    with pytest.raises(ValueError, match="Discount must be between 0 and 100"):
        calculate_discount(100, 150)

Example 2: JavaScript API Test

Input:

Copyasync function fetchUserData(userId) {
    const response = await fetch(`/api/users/${userId}`);
    if (!response.ok) throw new Error('Failed to fetch user');
    return response.json();
}

Output:

Copyimport { describe, it, expect, vi } from 'vitest';

describe('fetchUserData', () => {
    it('should fetch user data successfully', async () => {
        global.fetch = vi.fn(() =>
            Promise.resolve({
                ok: true,
                json: () => Promise.resolve({ id: 1, name: 'John' })
            })
        );

        const data = await fetchUserData(1);
        expect(data).toEqual({ id: 1, name: 'John' });
        expect(fetch).toHaveBeenCalledWith('/api/users/1');
    });

    it('should throw error when fetch fails', async () => {
        global.fetch = vi.fn(() =>
            Promise.resolve({ ok: false })
        );

        await expect(fetchUserData(1)).rejects.toThrow('Failed to fetch user');
    });
});

Notes

• Cover edge cases and error scenarios
• Use descriptive test names that explain what is being tested
• Keep tests isolated and independent
• Mock external dependencies
• Test both success and failure paths
• Follow the AAA pattern: Arrange, Act, Assert
• Consider performance and testing pyramid principles