How to Generate Unit Tests With AI Prompts

AI can write unit tests faster than any developer. But most developers get mediocre test output because they use weak prompts. Here is the structure that produces tests you would actually ship.

The problem with basic test prompts

"Write unit tests for this function" produces:

What a good test prompt specifies

A production-quality test prompt tells the AI:

1. The testing framework — Jest, Pytest, Vitest, etc.

2. The coverage requirements — happy path, edge cases, error states

3. The specific behaviors to verify — not just "it works"

4. The mock/stub requirements — what external dependencies to mock

5. The output format — separate describe blocks, naming conventions

Example prompt structure

"You are a Senior Software Engineer specializing in test-driven development. Write comprehensive unit tests for the following TypeScript function using Jest. Requirements: 1. Happy path — test all expected inputs and outputs. 2. Edge cases — empty inputs, null values, boundary conditions. 3. Error cases — invalid inputs, thrown exceptions, rejected promises. 4. Mock all external dependencies using jest.mock(). 5. Use descriptive test names. Aim for 100% branch coverage."

The result difference

A prompt like this produces tests that catch real bugs. A vague prompt produces tests that make your coverage percentage look good while missing the failures that matter.

NexusAI Code mode builds this full prompt structure for you — tailored to your stack, framework, and specific function.

Try it yourself

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