Test Generator logo

Test Generator

Organization
AIDotNet
test-generator

自动生成全面的测试套件,包括单元测试、集成测试和E2E测试,支持Jest、Vitest、pytest、xUnit等。

Overview

PublisherAIDotNet
RepositoryMoYuCode
Skill nametest-generator
Stars
85
Forks
17
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by AIDotNet on GitHub. Read the source before you install it.

Installation

Install the Test Generator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AIDotNet/MoYuCode.git /tmp/MoYuCode
mkdir -p .claude/skills
cp -r /tmp/MoYuCode/skills/community/test-generator .claude/skills/test-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Test Generator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Test Generator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Test Generator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Test Generator Skill

Description

Generate comprehensive test suites with unit tests, integration tests, mocks, and edge case coverage.

Trigger

  • /test command
  • User requests test generation
  • User needs test coverage

Prompt

You are a testing expert that creates comprehensive test suites.

Jest/Vitest Unit Tests (TypeScript)

typescript
import { describe, it, expect, vi, beforeEach } from 'vitest';
import { UserService } from './UserService';
import { UserRepository } from './UserRepository';

// Mock the repository
vi.mock('./UserRepository');

describe('UserService', () => {
  let userService: UserService;
  let mockRepository: jest.Mocked<UserRepository>;

  beforeEach(() => {
    mockRepository = new UserRepository() as jest.Mocked<UserRepository>;
    userService = new UserService(mockRepository);
    vi.clearAllMocks();
  });

  describe('createUser', () => {
    it('should create a user with valid data', async () => {
      // Arrange
      const userData = { email: 'test@example.com', name: 'Test User' };
      const expectedUser = { id: '123', ...userData, createdAt: new Date() };
      mockRepository.create.mockResolvedValue(expectedUser);

      // Act
      const result = await userService.createUser(userData);

      // Assert
      expect(result).toEqual(expectedUser);
      expect(mockRepository.create).toHaveBeenCalledWith(userData);
      expect(mockRepository.create).toHaveBeenCalledTimes(1);
    });

    it('should throw error for duplicate email', async () => {
      // Arrange
      const userData = { email: 'existing@example.com', name: 'Test' };
      mockRepository.create.mockRejectedValue(new Error('DUPLICATE_EMAIL'));

      // Act & Assert
      await expect(userService.createUser(userData))
        .rejects.toThrow('DUPLICATE_EMAIL');
    });

    it('should validate email format', async () => {
      // Arrange
      const invalidData = { email: 'invalid-email', name: 'Test' };

      // Act & Assert
      await expect(userService.createUser(invalidData))
        .rejects.toThrow('INVALID_EMAIL');
    });
  });

  describe('getUserById', () => {
    it('should return user when found', async () => {
      const user = { id: '123', email: 'test@example.com', name: 'Test' };
      mockRepository.findById.mockResolvedValue(user);

      const result = await userService.getUserById('123');

      expect(result).toEqual(user);
    });

    it('should return null when user not found', async () => {
      mockRepository.findById.mockResolvedValue(null);

      const result = await userService.getUserById('nonexistent');

      expect(result).toBeNull();
    });
  });
});

pytest (Python)

python
import pytest
from unittest.mock import Mock, patch
from user_service import UserService

class TestUserService:
    @pytest.fixture
    def mock_repository(self):
        return Mock()

    @pytest.fixture
    def user_service(self, mock_repository):
        return UserService(mock_repository)

    def test_create_user_success(self, user_service, mock_repository):
        # Arrange
        user_data = {"email": "test@example.com", "name": "Test User"}
        expected = {"id": "123", **user_data}
        mock_repository.create.return_value = expected

        # Act
        result = user_service.create_user(user_data)

        # Assert
        assert result == expected
        mock_repository.create.assert_called_once_with(user_data)

    def test_create_user_duplicate_email(self, user_service, mock_repository):
        mock_repository.create.side_effect = ValueError("DUPLICATE_EMAIL")

        with pytest.raises(ValueError, match="DUPLICATE_EMAIL"):
            user_service.create_user({"email": "existing@example.com"})

    @pytest.mark.parametrize("invalid_email", [
        "invalid",
        "@example.com",
        "test@",
        "",
    ])
    def test_validate_email_invalid(self, user_service, invalid_email):
        with pytest.raises(ValueError, match="INVALID_EMAIL"):
            user_service.create_user({"email": invalid_email, "name": "Test"})

xUnit (C#)

csharp
public class UserServiceTests
{
    private readonly Mock<IUserRepository> _mockRepository;
    private readonly UserService _userService;

    public UserServiceTests()
    {
        _mockRepository = new Mock<IUserRepository>();
        _userService = new UserService(_mockRepository.Object);
    }

    [Fact]
    public async Task CreateUser_WithValidData_ReturnsUser()
    {
        // Arrange
        var userData = new CreateUserDto { Email = "test@example.com", Name = "Test" };
        var expectedUser = new User { Id = Guid.NewGuid(), Email = userData.Email };
        _mockRepository.Setup(r => r.CreateAsync(It.IsAny<User>()))
            .ReturnsAsync(expectedUser);

        // Act
        var result = await _userService.CreateUserAsync(userData);

        // Assert
        Assert.Equal(expectedUser.Email, result.Email);
        _mockRepository.Verify(r => r.CreateAsync(It.IsAny<User>()), Times.Once);
    }

    [Theory]
    [InlineData("")]
    [InlineData("invalid")]
    [InlineData("@example.com")]
    public async Task CreateUser_WithInvalidEmail_ThrowsValidationException(string email)
    {
        var userData = new CreateUserDto { Email = email, Name = "Test" };

        await Assert.ThrowsAsync<ValidationException>(
            () => _userService.CreateUserAsync(userData));
    }
}

Tags

testing, unit-tests, integration-tests, tdd, quality-assurance

Compatibility

  • Codex: ✅
  • Claude Code: ✅

Frequently asked questions

What does the Test Generator AI skill do?

自动生成全面的测试套件,包括单元测试、集成测试和E2E测试,支持Jest、Vitest、pytest、xUnit等。

Why use Test Generator on TypingMind?

Because you install it once and use it with any model. Test Generator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Test Generator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AIDotNet/MoYuCode/tree/main/skills/community/test-generator. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Test Generator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Test Generator?

As many as you like. As long as a model supports skills, you can use Test Generator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Test Generator AI skill free?

Yes. It is published on GitHub by AIDotNet under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇