AI Test Generation Prompt
Generates behavioural tests and edge cases, not tautologies.
/ quick answer
Use when adding coverage to existing code or a new AI feature. Generates behavioural tests and edge cases, not tautologies.
Generate tests for the code below. Rules:
- Test behaviour and contracts, never implementation details.
- No snapshot tests of model output.
- Include edge cases: empty, null, malformed, boundary, concurrent, very large input.
- For AI features, assert structure and required facts, not exact wording.
- Each test name states the behaviour being guaranteed.
Return:
1. The test file, runnable in {{TEST_FRAMEWORK}}.
2. A list of behaviours you could NOT test and why.
3. Bugs you noticed in the code while writing the tests.
Code: {{CODE}}
Expected behaviour: {{BEHAVIOUR}}1. describe('parseInvoice') → it('rejects a document whose line items do not sum to the total').../ frequently asked
What does the AI Test Generation Prompt prompt do?
Use when adding coverage to existing code or a new AI feature.
Which AI models work with this prompt?
It is model-agnostic: it works with any capable general model. Replace the bracketed variables with your own context before running it.
How do I use this prompt?
1) Copy the prompt with the copy button. 2) Replace every bracketed variable with your real details. 3) Paste it into your AI assistant. 4) Compare the answer with the example output and ask for changes if needed.
What output should I expect?
1. describe('parseInvoice') → it('rejects a document whose line items do not sum to the total')...
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →AI Testing
AI testing covers two things: using AI to generate and maintain tests, and testing AI systems whose output is non-deterministic.
Related workflows
Turn this into a repeatable process.
- →Build a Test Suite for a Non-Deterministic AI Feature
Grade probabilistic output without brittle snapshot tests.
Related tool stacks
The tools that run it in production.
- →AI Testing Stack
Test deterministic code and probabilistic AI output in one pipeline.
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