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Testing48k · #4443

unit-testing-test-generate

Has your agent generate comprehensive and maintainable unit tests. It ensures code works correctly by covering common cases and unexpected situations.

What it does

This tool creates automatic tests for your code. It analyzes the code you provide and generates tests that check if it works correctly, including unusual situations.

When to use it

  • ✓When you have finished code and want to ensure it works.
  • ✓When you want your code's tests to be done consistently.
  • ✓When you need to test specific scenarios and rare cases.

Example of what to ask your AI

“Generate unit tests for this Python function that calculates the average of a list of numbers.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/unit-testing-test-generate/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/unit-testing-test-generate/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool reads your code, identifies parts that need testing, and creates test files. It uses techniques to ensure tests cover as much code as possible and check for errors.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add sickn33/agentic-awesome-skills --skill unit-testing-test-generate

Or download just the file:

curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/unit-testing-test-generate/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Automated Unit Test Generation

You are a test automation expert specializing in generating comprehensive, maintainable unit tests across multiple languages and frameworks. Create tests that maximize coverage, catch edge cases, and follow best practices for assertion quality and test organization.

Use this skill when

  • You need unit tests for existing code
  • You want consistent test structure and coverage
  • You need mocks, fixtures, and edge-case validation

Do not use this skill when

  • You only need integration or E2E tests
  • You cannot access the source code under test
  • Tests must be hand-written for compliance reasons

Context

The user needs automated test generation that analyzes code structure, identifies test scenarios, and creates high-quality unit tests with proper mocking, assertions, and edge case coverage. Focus on framework-specific patterns and maintainable test suites.

Requirements

$ARGUMENTS

Instructions

1. Analyze Code for Test Generation

Scan codebase to identify untested code and generate comprehensive test suites:

import ast
from pathlib import Path
from typing import Dict, List, Any

class TestGenerator:
    def __init__(self, language: str):
        self.language = language
        self.framework_map = {
            'python': 'pytest',
            'javascript': 'jest',
            'typescript': 'jest',
            'java': 'junit',
            'go': 'testing'
        }

    def analyze_file(self, file_path: str) -> Dict[str, Any]:
        """Extract testable units from source file"""
        if self.language == 'python':
            return self._analyze_python(file_path)
        elif self.language in ['javascript', 'typescript']:
            return self._analyze_javascript(file_path)

    def _analyze_python(self, file_path: str) -> Dict:
        with open(file_path) as f:
            tree = ast.parse(f.read())

        functions = []
        classes = []

        for node in ast.walk(tree):
            if isinstance(node, ast.FunctionDef):
                functions.append({
                    'name': node.name,
                    'args': [arg.arg for arg in node.args.args],
                    'returns': ast.unparse(node.returns) if node.returns else None,
                    'decorators': [ast.unparse(d) for d in node.decorator_list],
                    'docstring': ast.get_docstring(node),
                    'complexity': self._calculate_complexity(node)
                })
            elif isinstance(node, ast.ClassDef):
                methods = [n.name for n in node.body if isinstance(n, ast.FunctionDef)]
                classes.append({
                    'name': node.name,
                    'methods': methods,
                    'bases': [ast.unparse(base) for base in node.bases]
                })

        return {'functions': functions, 'classes': classes, 'file': file_path}

2. Generate Python Tests with pytest

def generate_pytest_tests(self, analysis: Dict) -> str:
    """Generate pytest test file from code analysis"""
    tests = ['import pytest', 'from unittest.mock import Mock, patch', '']

    module_name = Path(analysis['file']).stem
    tests.append(f"from {module_name} import *\n")

    for func in analysis['functions']:
        if func['name'].startswith('_'):
            continue

        test_class = self._generate_function_tests(func)
        tests.append(test_class)

    for cls in analysis['classes']:
        test_class = self._generate_class_tests(cls)
        tests.append(test_class)

    return '\n'.join(tests)

def _generate_function_tests(self, func: Dict) -> str:
    """Generate test cases for a function"""
    func_name = func['name']
    tests = [f"\n\nclass Test{func_name.title()}:"]

    # Happy path test
    tests.append(f"    def test_{func_name}_success(self):")
    tests.append(f"        result = {func_name}({self._generate_mock_args(func['args'])})")
    tests.append(f"        assert result is not None\n")

    # Edge case tests
    if len(func['args']) > 0:
        tests.append(f"    def test_{func_name}_with_empty_input(self):")
        tests.append(f"        with pytest.raises((ValueError, TypeError)):")
        tests.append(f"            {func_name}({self._generate_empty_args(func['args'])})\n")

    # Exception handling test
    tests.append(f"    def test_{func_name}_handles_errors(self):")
    tests.append(f"        with pytest.raises(Exception):")

…
FAQ

What are unit tests?

They are small tests that check if a specific part of the code (like a function) works as expected, in isolation.

Why use this tool?

It saves time and ensures tests are comprehensive and consistent, helping to find bugs earlier.

Does it work for any programming language?

The tool supports several popular languages like Python, JavaScript, TypeScript, Java, and Go.

Details

Original description by the author

Generate comprehensive, maintainable unit tests across languages with strong coverage and edge case focus.

repo: sickn33/agentic-awesome-skills

Popularity

GitHub stars
48k
Ranking position
#4443
License
MIT
Updated
10/15/2026

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