Skip to content
Try ZeroTell

ZeroTell Pro is an auto-renewing subscription, billed weekly, monthly or yearly. Cancel anytime in Dashboard → Subscription. See plans and prices.

Built for students, writers and researchers

AI Code Detector by ZeroTell · evidence you can check

Paste a function, a file or a whole assignment. We measure the style habits AI assistants tend to leave behind, ask a model to review the code line by line, and show you exactly why the estimate came out the way it did.

0 lines of code

AI-likelihood signal

This is a signal, not proof. Clean, well-commented code written by a careful person can look "AI-like", and edited AI code can look human. Never accuse anyone on the strength of this report alone.

Your report will appear here: a likelihood band, notes on specific lines and every style signal we measured.

How the AI Code Detector works

  1. Paste code or upload a file

    Python, JavaScript, TypeScript, Java, C, C++, C#, Go, Rust, PHP, Ruby, Kotlin, Swift and SQL are recognized automatically. You can also pick the language yourself.

  2. We measure style habits

    Comment density and phrasing, naming consistency, scaffolding, docstring templates, defensive error handling and line-length spread are counted the same way every time.

  3. A model reviews the code

    It reads the numbered code alongside those measurements and writes short notes on the lines that stand out, for and against AI generation.

  4. You get a band and the reasons

    The result is low, medium or high likelihood, never a fake precise percentage, with the evidence listed so you can judge it yourself.

What the report shows

  • A likelihood band

    Low, medium or high. Code style is not a fingerprint, so a percentage would claim precision that no detector has.

  • Measured style signals

    Each signal states what was counted, such as how many comments narrate the code, so the estimate is never a black box.

  • Line-by-line notes

    The review points at concrete regions, like a templated docstring or a generic error print, with their line numbers.

  • Human-looking evidence too

    Terse comments, TODOs with context and inconsistent naming count towards human authorship and are reported as well.

Who uses it

  • Computer science teachers

    Get a starting point for a conversation with a student, together with specific lines to ask them about.

  • Students

    See which habits in your own code could make it look generated before you hand it in.

  • Hiring teams

    Review take-home tasks with evidence you can discuss in the follow-up interview rather than a bare score.

  • Open-source maintainers

    Spot contributions that may need a closer look at licensing and test coverage.

More ways to check work

Frequently asked questions

No. No tool can. The report is a signal based on style habits, and experienced developers who comment carefully and follow a style guide often produce code that looks "AI-like". Use it to decide what to ask about, not as evidence on its own.

A percentage suggests a precision that style analysis cannot deliver. Low, medium and high describe honestly how strongly the signals point one way.

Comment density, comment phrasing, naming uniformity, boilerplate such as example-usage blocks, templated docstrings, error-handling verbosity and how evenly line lengths are spread. Each one is shown with the numbers behind it.

Python, JavaScript, TypeScript, Java, C, C++, C#, Go, Rust, PHP, Ruby, Kotlin, Swift and SQL are detected automatically. Other languages still get the model review and the language-neutral signals.

Not on the Pro plans* (*fair use: up to 300 runs a day across the writing, study and code tools). Without a plan, each check uses 2 credits. A ZeroTell account is needed. You can check up to 20,000 characters at a time.

Uploaded files are read in your browser and sent as text for the check. Your code is sent to our AI provider for the review and is not published or added to any database.

See the evidence, then decide

Paste code and get a likelihood band with the reasons behind it.

Check code