Test Driven Development

What it does

This skill enables AI agents to write and execute tests before writing code, following a Test-Driven Development (TDD) workflow. It facilitates creating automated unit tests that verify specific functionalities, ensuring code quality and reducing debugging time. The agent can generate test cases based on requirements or user stories, and then implement the corresponding functionality.

When to use it

• New Feature Implementation: Use when developing new features for an application where you want to ensure correctness from the start.
• Refactoring Existing Code: Apply TDD during refactoring to guarantee that changes don't break existing functionality.
• Bug Fixing: Write tests to reproduce and verify fixes, preventing regressions.
• Complex Logic Development: When dealing with intricate algorithms or business rules, TDD helps clarify requirements and build confidence in the implementation.

Key capabilities

• Test case generation based on requirements
• Automated test execution
• Red-Green-Refactor workflow support
• Unit testing framework integration

Example prompts

• "Write a failing test for a function that calculates the sum of two numbers."
• "Generate tests to cover all edge cases for validating user input in a form."
• "Implement the 'calculate_discount' function based on these tests: [list of tests]."

Tips & gotchas

The agent requires access to a testing framework (e.g., JUnit, pytest) and appropriate development environment setup to execute generated tests. Ensure that the AI has sufficient context regarding the project’s architecture and coding standards for optimal results.