AI Phrase Checker
Paste text, see which AI-writing patterns it contains. Vocabulary tells, negative parallelisms, em-dash overuse, chatbot leftovers. English and German, all in your browser.
Verdict
Heavy AI patterns
Patterns found
7
Per 100 words
19.4
Highlights
Findings
- AI vocabulary×4
High-frequency LLM words. Use plain words instead.
digital landscape · testament to · seamless · groundbreaking
- Throat-clearing×1
"It's important to note" and friends. Just say the thing.
It's important to note
- Negative parallelism×1
"Not just X, it's Y" constructions. Say Y.
not just about automation, but
- Vague attribution×1
Name the source or cut the claim.
experts say
How it works
This is a pattern lint, not a detector. It scans your text against word lists and phrase patterns that show up constantly in LLM output: "delve", "tapestry", "testament to", "it's important to note", "not just X, but Y", "experts say", em-dashes every second sentence. The German set covers the local equivalents ("entscheidend", "nicht nur... sondern", "zusammenfassend lässt sich sagen").
Matches get highlighted in the text and grouped into a findings list with a count per pattern. The verdict is a simple density score: patterns per 100 words. The language is detected from the text itself, so you can paste German and English drafts back to back without touching a switch.
The lists come from Wikipedia's "Signs of AI-generated writing" project, which I use in my own editing workflow. They get updated as the telltale vocabulary shifts, because it does shift.
What it can't do
Tell you whether a text was written by AI. Nobody can do that reliably, and tools that claim otherwise are selling confidence they don't have. A human who writes corporate marketing copy will light this thing up, and a carefully edited AI text will pass it clean.
What the score does tell you: whether a text reads like AI output. That's the thing that costs you credibility with readers, regardless of who actually wrote it.
When to use it
- Checking a draft before publishing, especially one an LLM helped with.
- Editing AI output for a client and wanting a quick list of the obvious tells.
- Settling the "this sounds like ChatGPT" argument with something more specific than a feeling.
Everything runs locally. Your text never leaves the browser, which matters when the draft is client work.