Using Tests

The using-tests skill enables AI agents to generate, execute, and analyze automated test suites directly within code repositories. It ensures software reliability by creating unit, integration, and end-to-end tests that validate logic against expected outcomes.

When to use it

• Regression Prevention: Automatically generate test cases when modifying existing functions to prevent unintended side effects.
• Code Review Validation: Run a suite of tests before merging pull requests to guarantee code stability.
• Edge Case Discovery: Identify missing scenarios by having the agent create specific boundary condition tests for complex logic.
• Documentation Verification: Ensure that API documentation examples are functional by generating corresponding integration tests.

Key capabilities

• Generates test files in multiple languages (e.g., Jest, PyTest, JUnit).
• Analyzes source code to infer dependencies and required mock objects.
• Executes test suites and reports pass/fail status with detailed error logs.
• Refactors failing tests to align with updated application logic.

Example prompts

• "Generate a comprehensive unit test suite for the calculateDiscount function using Jest."
• "Run all integration tests in the api/ directory and summarize any failures."
• "Create an end-to-end test scenario that verifies user login and dashboard rendering."

Tips & gotchas

Ensure your AI agent has read access to the project's dependency files (like package.json or requirements.txt) to correctly configure the testing environment. If tests fail due to missing data, instruct the agent to create necessary mock fixtures before execution.