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Mocking Test Generator

Community
ArabelaTso
mocking-test-generator

Generate unit tests with proper mocking for Python (unittest.mock/pytest) or Java (Mockito/JUnit) code. Use when users request test generation, unit tests with mocks, or testing code that has external dependencies like database calls, API requests, file I/O, or network operations. Automatically identifies dependencies to mock and creates executable, maintainable test code.

Overview

PublisherArabelaTso
RepositorySkills-4-SE
Skill namemocking-test-generator
Stars
258
Forks
25
Bundled files
2
LicenseApache-2.0
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Mocking 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.
    https://github.com/ArabelaTso/Skills-4-SE/tree/main/skills/mocking-test-generator
  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/ArabelaTso/Skills-4-SE.git /tmp/Skills-4-SE
mkdir -p .claude/skills
cp -r /tmp/Skills-4-SE/skills/mocking-test-generator .claude/skills/mocking-test-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mocking 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 Mocking 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 Mocking 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.

Mocking Test Generator

Generate unit tests with proper mocking of external dependencies for Python and Java code.

Workflow

  1. Analyze the code - Identify external dependencies, side effects, and testable units
  2. Select framework - Determine Python (unittest.mock/pytest) or Java (Mockito/JUnit)
  3. Generate mocks - Create mock objects for external dependencies
  4. Write tests - Generate executable test code with assertions
  5. Add documentation - Include clear comments explaining mocks and test logic

Step 1: Analyze the Code

Read the target code to identify:

  • External dependencies: API clients, database connections, third-party libraries
  • I/O operations: File reads/writes, network requests, system calls
  • Side effects: Email sending, logging, state modifications
  • Testable units: Functions, methods, or classes to test in isolation

Ask clarifying questions if:

  • Multiple functions/classes exist (which to test?)
  • Testing scope is unclear (unit vs integration?)
  • Mock behavior needs specification (return values, exceptions?)

Step 2: Select Framework

Python: Use unittest.mock with pytest or unittest

  • Prefer @patch decorator for external calls
  • Use Mock() objects for complex dependencies
  • Apply pytest.fixture for reusable mocks

Java: Use Mockito with JUnit 5

  • Use @Mock annotation for dependencies
  • Apply @ExtendWith(MockitoExtension.class) to test class
  • Use when().thenReturn() for stubbing

Step 3: Generate Mocks

Identify what to mock:

Always mock:

  • External API calls (HTTP requests, REST clients)
  • Database connections and queries
  • File system operations
  • Network I/O
  • Time/date functions
  • Random number generators
  • Environment variables

Never mock (unless explicitly requested):

  • Internal business logic
  • Pure functions
  • Data structures
  • Simple utilities

For common patterns, reference:

Step 4: Write Tests

Generate test code that:

  1. Imports - Include necessary testing and mocking libraries
  2. Setup - Initialize mocks and test fixtures
  3. Execution - Call the function/method under test
  4. Assertions - Verify expected behavior and outputs
  5. Verification - Confirm mocks were called correctly

Test structure:

python
# Python example
from unittest.mock import patch, Mock
import pytest

@patch('module.external_dependency')
def test_function_name(mock_dependency):
    # Arrange: Setup mock behavior
    mock_dependency.return_value = expected_value

    # Act: Execute function under test
    result = function_under_test(input_data)

    # Assert: Verify results
    assert result == expected_output
    mock_dependency.assert_called_once_with(expected_args)
java
// Java example
@ExtendWith(MockitoExtension.class)
class ServiceTest {
    @Mock
    private ExternalDependency dependency;

    @Test
    void testMethodName() {
        // Arrange: Setup mock behavior
        when(dependency.method()).thenReturn(expectedValue);

        // Act: Execute method under test
        Service service = new Service(dependency);
        String result = service.methodUnderTest();

        // Assert: Verify results
        assertEquals(expectedOutput, result);
        verify(dependency).method();
    }
}

Include:

  • Multiple test cases for different scenarios (happy path, edge cases, errors)
  • Descriptive test names that explain what is being tested
  • Setup/teardown if needed for test isolation

Step 5: Add Documentation

Include comments that explain:

  • What external dependency is being mocked and why
  • What behavior the mock simulates
  • What the test verifies

Keep comments concise and focused on non-obvious aspects.

Output Format

Provide:

  1. Complete test file - Fully executable with all imports
  2. Test class/module - Properly structured for the framework
  3. Multiple test methods - Cover main scenarios
  4. Clear naming - Descriptive test and variable names

Do not:

  • Modify the original code under test
  • Mock internal logic unless explicitly requested
  • Generate incomplete or pseudo-code tests

Example Usage

User request: "Generate unit tests for this Python function that calls an external API"

Response:

  1. Read the function code
  2. Identify the API call to mock
  3. Generate pytest test file with @patch decorator
  4. Include tests for success case, error handling, and edge cases
  5. Add comments explaining the mock setup

Framework-Specific Notes

Python (pytest):

  • Use @pytest.fixture for reusable mock setups
  • Apply @patch as decorator or context manager
  • Use mock_open for file operations
  • Apply @patch.dict for environment variables

Python (unittest):

  • Use unittest.TestCase base class
  • Apply @patch decorator or patch() context manager
  • Use setUp() and tearDown() methods
  • Call self.assert* methods

Java (Mockito + JUnit 5):

  • Use @ExtendWith(MockitoExtension.class) on test class
  • Apply @Mock for dependencies
  • Use @BeforeEach for setup, @AfterEach for teardown
  • Apply ArgumentCaptor to verify complex arguments
  • Use MockedStatic for static method mocking (Mockito 3.4+)

Common Patterns

Reference files contain detailed examples for:

Python (references/python_patterns.md):

  • External API calls
  • Database operations
  • File system operations
  • Environment variables
  • Time-dependent code
  • Exception handling

Java (references/java_patterns.md):

  • External API calls
  • Database operations
  • File system operations
  • Void methods
  • Exception handling
  • Argument captors
  • Static method mocking
  • Constructor mocking

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Mocking Test Generator AI skill do?

Generate unit tests with proper mocking for Python (unittest.mock/pytest) or Java (Mockito/JUnit) code. Use when users request test generation, unit tests with mocks, or testing code that has external dependencies like database calls, API requests, file I/O, or network operations. Automatically identifies dependencies to mock and creates executable, maintainable test code.

Why use Mocking Test Generator on TypingMind?

Because you install it once and use it with any model. Mocking 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 Mocking Test Generator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ArabelaTso/Skills-4-SE/tree/main/skills/mocking-test-generator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Mocking 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 Mocking Test Generator?

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

Is the Mocking Test Generator AI skill free?

Yes. It is published on GitHub by ArabelaTso under the Apache-2.0 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.

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