Summary

This AI unit test generator builds a ready-to-edit test scaffold from your function name, parameters, and behavior: pick Jest, Vitest, pytest, or Go, and it applies the Arrange-Act-Assert pattern with framework-accurate syntax. It also suggests edge cases, null input, empty input, boundary values, and wrong types, drawn from equivalence partitioning and boundary value analysis, so you do not have to remember which inputs actually need a test. It does not call an AI model or run your code: the assertions are marked TODO because only you know the real expected values. Free, no signup, runs entirely in your browser.

AI Unit Test Generator for Jest, Pytest, and Go

Describe your function, pick a language and framework, and get an Arrange-Act-Assert test scaffold plus a checklist of edge cases to cover before you ship.

Build a test scaffold

Unit test scaffold generator

Fill in your function's name, parameters, and behavior. The scaffold updates as you type, in the syntax of the framework you picked.

Edge cases to cover
Generated test scaffold
Test cases covered

    This builds a syntax-correct scaffold using the Arrange-Act-Assert pattern. It does not run your code or invent business logic: fill in the real values and assertions before you commit.

    How it works

    How this generator builds your tests

    Arrange-Act-Assert structure

    Every generated test follows the AAA pattern: set up your inputs, call the function, then assert the result. It is the same structure used in most Jest, Vitest, and pytest codebases, so the output drops into an existing suite without rework.

    Framework-accurate syntax

    Pick Jest, Vitest, pytest, or Go's testing package and the scaffold matches that framework's real syntax: describe/it/expect blocks, def test_ functions with pytest.raises, or t.Run subtests built on a (value, error) return.

    Edge cases from real test design

    The checklist, null input, empty input, boundary values, wrong types, comes from equivalence partitioning and boundary value analysis, the heuristics testers use to decide which inputs are actually worth a test.

    Example

    What the generator produces

    Type a function name like calculateTotal, list its parameters, mark it as throwing on invalid input, and check a couple of edge cases. The panel on the right rewrites itself with a full describe block, or a pytest / Go test file, matched to your framework's real syntax. Every test keeps the Arrange, Act, and Assert sections as separate, commented steps, so a reviewer can tell at a glance what each test actually checks instead of parsing one dense block of setup code. The assertion lines are marked with a TODO comment on purpose: the scaffold does not guess what your function should return, it only builds the shape of the test around a value you fill in.

    Laptop screen showing a blurred code editor with a passing test suite

    Common questions

    Is this free to use?
    Yes. The generator runs entirely in your browser: no signup, no API key, and no usage limit. Nothing you type is sent to a server except an anonymous page-view beacon.
    Does this call a real AI model to write my tests?
    No. It is a rule-based scaffold builder, not an LLM. It applies the Arrange-Act-Assert pattern and your framework's real syntax to the function name, parameters, and edge cases you provide. That keeps the output predictable and fast, but it does not understand your business logic.
    How accurate are the generated tests?
    The structure and syntax are correct for the framework you pick. The assertions are placeholders marked TODO: you still need to fill in the exact expected values, because only you know what your function is supposed to return.
    Which languages and frameworks are supported?
    JavaScript with Jest or Vitest, TypeScript with Vitest, Python with pytest, and Go with the standard testing package. Each output matches that framework's real conventions, including Go's (value, error) return pattern for functions that can fail.
    Why does the null or boundary case sometimes look unfinished?
    Those cases are intentionally left as scaffolds instead of guessed assertions. Whether a null input should throw, return a default, or do something else depends on your function, not on this tool.
    Can I use this for a function that takes objects, not primitives?
    Yes. Type the parameter names and the generator produces the right structure. You will still need to replace the placeholder values, like 'example' or 2, with real objects that match your actual types.
    Does this replace writing tests myself?
    No. Think of it as the first ten minutes of writing a test file: naming, structure, and the edge cases worth checking. The assertions and the judgment calls about expected behavior are still yours.
    Why should I bother with unit tests before a rollout?
    A unit test that catches a bad edge case locally is a lot cheaper than the same bug reaching a canary release or a percentage rollout. It will not catch every failure mode on its own, but it shrinks the list of things that can only be found in production.

    Ship tests that catch bugs before your rollout does

    Pair better unit tests with SLO-gated rollouts and auto-rollback, so what slips past your tests still fails safe in production.

    See how Upstream gates a rollout