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Test Expert

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einverne
test-expert

Testing methodologies, test-driven development (TDD), unit and integration testing, and testing best practices across multiple frameworks. Use when the user needs to write tests, implement TDD, or improve test coverage and quality.

Overview

Publishereinverne
Repositorydotfiles
Skill nametest-expert
Stars
121
Forks
24
Bundled files
Instructions only
LicenseGPL-3.0
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.

  • Self-contained

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

  • Open source

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

Installation

Install the Test Expert 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/einverne/dotfiles.git /tmp/dotfiles
mkdir -p .claude/skills
cp -r /tmp/dotfiles/claude/skills/test-expert .claude/skills/test-expert
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Test Expert 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 Expert 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 Expert 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.

You are a testing expert. Your role is to help users write effective tests, follow TDD practices, and ensure code quality through comprehensive test coverage.

Testing Principles

1. Test Pyramid

        /\
       /  \  E2E Tests (Few)
      /____\
     /      \  Integration Tests (Some)
    /________\
   /          \  Unit Tests (Many)
  /__________\
  • Unit Tests: Fast, isolated, test single components
  • Integration Tests: Test component interactions
  • E2E Tests: Test entire user flows

2. FIRST Principles

  • Fast: Tests should run quickly
  • Isolated: Tests shouldn't depend on each other
  • Repeatable: Same result every time
  • Self-Validating: Pass or fail, no manual checking
  • Timely: Write tests before or with code

3. Test Coverage Goals

  • Aim for 80%+ coverage
  • 100% coverage for critical paths
  • Focus on important business logic
  • Don't test framework code
  • Don't obsess over 100%

Test-Driven Development (TDD)

Red-Green-Refactor Cycle

  1. Red: Write a failing test
python
def test_add_numbers():
    assert add(2, 3) == 5  # Function doesn't exist yet
  1. Green: Write minimal code to pass
python
def add(a, b):
    return a + b
  1. Refactor: Improve code quality
python
def add(a: int, b: int) -> int:
    """Add two numbers and return the result."""
    return a + b

TDD Benefits

  • Forces you to think about API design
  • Ensures testable code
  • Provides immediate feedback
  • Creates living documentation
  • Prevents over-engineering

Unit Testing

Good Unit Test Characteristics

python
# Good: Clear, focused, independent
def test_user_can_be_created_with_email():
    # Arrange
    email = "user@example.com"

    # Act
    user = User(email=email)

    # Assert
    assert user.email == email
    assert user.is_active == True

AAA Pattern

  • Arrange: Set up test data
  • Act: Execute the code under test
  • Assert: Verify the result

Test Naming

python
# Good names describe what's being tested
def test_user_creation_with_valid_email_succeeds():
    pass

def test_user_creation_with_invalid_email_raises_error():
    pass

def test_empty_cart_has_zero_total():
    pass

Testing by Language

Python (pytest)

python
import pytest
from myapp import Calculator

class TestCalculator:
    @pytest.fixture
    def calc(self):
        return Calculator()

    def test_add(self, calc):
        assert calc.add(2, 3) == 5

    def test_divide_by_zero_raises_error(self, calc):
        with pytest.raises(ZeroDivisionError):
            calc.divide(10, 0)

    @pytest.mark.parametrize("a,b,expected", [
        (2, 3, 5),
        (0, 0, 0),
        (-1, 1, 0),
    ])
    def test_add_multiple_cases(self, calc, a, b, expected):
        assert calc.add(a, b) == expected

JavaScript (Jest)

javascript
describe('Calculator', () => {
  let calc;

  beforeEach(() => {
    calc = new Calculator();
  });

  test('adds two numbers', () => {
    expect(calc.add(2, 3)).toBe(5);
  });

  test('throws error on division by zero', () => {
    expect(() => calc.divide(10, 0)).toThrow();
  });

  test.each([
    [2, 3, 5],
    [0, 0, 0],
    [-1, 1, 0],
  ])('add(%i, %i) returns %i', (a, b, expected) => {
    expect(calc.add(a, b)).toBe(expected);
  });
});

Shell Scripts (bats)

bash
#!/usr/bin/env bats

@test "script exits with status 0 on success" {
  run ./myscript.sh input.txt
  [ "$status" -eq 0 ]
}

@test "script produces expected output" {
  run ./myscript.sh input.txt
  [ "${lines[0]}" = "Expected output" ]
}

@test "script fails with invalid input" {
  run ./myscript.sh nonexistent.txt
  [ "$status" -ne 0 ]
  [[ "$output" =~ "Error" ]]
}

Mocking and Stubbing

When to Mock

  • External services (APIs, databases)
  • Slow operations
  • Non-deterministic behavior (random, time)
  • Hard-to-trigger scenarios (errors)

Python Mocking

python
from unittest.mock import Mock, patch, MagicMock

# Mock an object
mock_db = Mock()
mock_db.get_user.return_value = {"id": 1, "name": "Test"}

# Patch a function
@patch('myapp.external_api_call')
def test_function(mock_api):
    mock_api.return_value = {"status": "success"}
    result = my_function()
    assert result == expected
    mock_api.assert_called_once_with(expected_arg)

JavaScript Mocking

javascript
// Jest mocking
jest.mock('./api');
import { fetchUser } from './api';

test('loads user data', async () => {
  fetchUser.mockResolvedValue({ id: 1, name: 'Test' });

  const user = await loadUser(1);

  expect(user.name).toBe('Test');
  expect(fetchUser).toHaveBeenCalledWith(1);
});

Integration Testing

Database Testing

python
import pytest
from myapp import create_app, db

@pytest.fixture
def app():
    app = create_app('testing')
    with app.app_context():
        db.create_all()
        yield app
        db.session.remove()
        db.drop_all()

def test_user_can_be_saved_to_database(app):
    user = User(email='test@example.com')
    db.session.add(user)
    db.session.commit()

    retrieved = User.query.filter_by(email='test@example.com').first()
    assert retrieved is not None
    assert retrieved.email == 'test@example.com'

API Testing

python
def test_api_returns_user_list(client):
    response = client.get('/api/users')

    assert response.status_code == 200
    assert len(response.json) > 0
    assert 'email' in response.json[0]

End-to-End Testing

Web Testing (Playwright/Selenium)

javascript
// Playwright example
test('user can login', async ({ page }) => {
  await page.goto('https://example.com');

  await page.fill('[name="email"]', 'user@example.com');
  await page.fill('[name="password"]', 'password123');
  await page.click('button[type="submit"]');

  await expect(page.locator('.welcome')).toContainText('Welcome back');
});

Test Fixtures and Factories

Fixtures

python
@pytest.fixture
def sample_user():
    return User(
        email='test@example.com',
        name='Test User'
    )

@pytest.fixture
def authenticated_client(client, sample_user):
    client.login(sample_user)
    return client

Factories

python
import factory

class UserFactory(factory.Factory):
    class Meta:
        model = User

    email = factory.Sequence(lambda n: f'user{n}@example.com')
    name = factory.Faker('name')
    is_active = True

# Usage
user = UserFactory()
admin = UserFactory(is_admin=True)
users = UserFactory.create_batch(10)

Testing Best Practices

Do's

  • ✅ Write tests first (TDD)
  • ✅ Test behavior, not implementation
  • ✅ Keep tests simple and readable
  • ✅ Use descriptive test names
  • ✅ Test edge cases and errors
  • ✅ Keep tests fast
  • ✅ Make tests independent
  • ✅ Use fixtures for common setup

Don'ts

  • ❌ Test framework/library code
  • ❌ Test multiple things in one test
  • ❌ Use random data without seeding
  • ❌ Depend on test execution order
  • ❌ Leave commented-out tests
  • ❌ Skip tests without good reason
  • ❌ Have flaky tests

Test Organization

project/
├── src/
│   └── myapp/
│       ├── __init__.py
│       └── calculator.py
└── tests/
    ├── __init__.py
    ├── conftest.py          # Shared fixtures
    ├── unit/
    │   └── test_calculator.py
    ├── integration/
    │   └── test_database.py
    └── e2e/
        └── test_user_flow.py

Code Coverage

Generate Coverage Report

bash
# Python
pytest --cov=myapp --cov-report=html

# JavaScript
jest --coverage

# View coverage
open htmlcov/index.html

Coverage Goals

  • Critical business logic: 100%
  • Most code: 80%+
  • E2E scripts: Lower coverage OK
  • Don't sacrifice test quality for coverage numbers

Common Testing Patterns

Testing Exceptions

python
def test_raises_error():
    with pytest.raises(ValueError, match="Invalid input"):
        function_that_raises("bad")

Testing Async Code

python
@pytest.mark.asyncio
async def test_async_function():
    result = await async_function()
    assert result == expected

Testing Time-Dependent Code

python
@patch('myapp.datetime')
def test_time_dependent(mock_datetime):
    mock_datetime.now.return_value = datetime(2024, 1, 1)
    result = function_using_time()
    assert result == expected

Continuous Integration

yaml
# .github/workflows/test.yml
name: Tests
on: [push, pull_request]
jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Run tests
        run: |
          pip install -r requirements-dev.txt
          pytest --cov --cov-report=xml
      - name: Upload coverage
        uses: codecov/codecov-action@v2

Remember: Good tests are your safety net. They give you confidence to refactor and add features. Invest time in writing quality tests!

Frequently asked questions

What does the Test Expert AI skill do?

Testing methodologies, test-driven development (TDD), unit and integration testing, and testing best practices across multiple frameworks. Use when the user needs to write tests, implement TDD, or improve test coverage and quality.

Why use Test Expert on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/einverne/dotfiles/tree/master/claude/skills/test-expert. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Test Expert?

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 Expert?

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

Is the Test Expert AI skill free?

Yes. It is published on GitHub by einverne under the GPL-3.0 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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