Twitter AI detector

1. 1

   Paste the post before you publish it. The check runs as you type, on posts, threads and replies.

2. 2

   Read the highlighted phrases. Each flag says what kind of tell it is and why readers notice it.

3. 3

   Replace the vague word with the real detail. Swap "powerful" for the number, "journey" for the actual step, and drop the closer.

Want drafts that sound like you from the start? Read how to test an AI tweet writer before you pay.

• It does not detect AI authorship. A person can write every flagged phrase, and a model can write a post with none of them.
• It checks a fixed list of phrases, so a paraphrased generic line will slip through.
• It works on English text only.
• It judges wording, not ideas. A clean post can still say nothing.

Is this a real AI detector for tweets?

It is a phrase check, not a model. It looks for the specific words, lines and punctuation that make a post read as AI-written, using the same list ClimbX flags in its own drafts. It cannot tell you who or what wrote a post. It tells you which parts will make readers think a machine did.

Why do these phrases make a post sound like AI?

Language models reach for the same safe, emphatic phrasing again and again: hype adjectives, brochure verbs and setup-and-reveal lines. After seeing them thousands of times, readers on X recognise the pattern in the first line and scroll past, even when a person wrote the post.

Is there a Twitter AI detector extension?

This tool is a web page, not an extension, so there is nothing to install. It works in any browser, including on your phone: paste the draft before you post it.

Is my text sent anywhere?

No. The check runs in your browser on the text you paste. Nothing is uploaded, stored or sent to an AI model.

Will removing the flagged phrases make my post perform better?

Not on its own. Removing them stops the post from reading as generic, which matters because generic posts get skimmed. What makes a post travel is a specific idea, number or question from your own experience. Use the flags as a prompt to replace a vague word with the real detail behind it.

Does it flag words people use normally?

Sometimes. "Massive" or "journey" can be literal, as in a massive outage or a user journey. Read each flag in context and keep the word when it is the most precise one.