Phrasing and vocabulary tells
A short list of words and phrases shows up constantly in AI-generated text: “delve into”, “it’s important to note”, “in today’s fast-paced world”, “boast” (as in “the app boasts a range of features”), “robust”, “tapestry”, “testament to”, “navigate the complexities of”. These became defaults because they’re safe and generic, they sound substantial without committing to anything specific, which is exactly what a model optimizing for plausible-sounding text tends to produce.
Watch the transition words too: “moreover”, “furthermore”, “additionally”, “in conclusion”, “that said”, stacked between nearly every paragraph. Human writing usually connects ideas with a plain “and”, “but”, or “so”, or nothing at all, letting one point follow another without narrating the connection. A document that formally announces every transition is doing more scaffolding than the ideas actually need.
The dash is a related tell, specifically its overuse as an all-purpose connector, standing in for a comma, colon, or period in sentence after sentence. One dash used well is ordinary punctuation. A document that reaches for it constantly, in place of every other kind of pause, is showing a habit rather than a stylistic choice.
Structural tells
Uniform sentence length across a whole document is one of the most reliable tells: human writing swings between short and long, focused and rambling, because attention and energy vary as a person writes. A document where every sentence runs to within a few words of the same length, paragraph after paragraph, reads smooth but mechanical.
Watch for listicle-brain hiding inside prose: paragraphs secretly organized into three neat, parallel points even when written as flowing sentences rather than a bulleted list. A topic sentence, three supporting points of roughly equal weight, and a tidy wrap-up sentence, repeated with the same shape across every section of a piece, is a structural fingerprint, not a coincidence.
Symmetric openings and closings are another: restating the question almost word-for-word at the start of an answer, then again as a summary at the end, as though the piece needs to prove it addressed the prompt on both sides of the content in the middle.
Rhetorical tells
Excessive hedging is a strong signal: “it could be argued that”, “some might say”, “it’s worth considering”, stacked so densely that no actual claim ever lands. Genuine writing usually commits to a position somewhere, even a modest one, because a person with a real view eventually says what they think.
A flattened emotional register is another: every topic gets the same even-handed, mildly positive treatment regardless of whether the subject actually has an obvious lean, with no real surprise, frustration, or specific enthusiasm about anything in particular.
None of these tells alone proves a document was AI-generated, a careful human writer can do any single one of them on a given day. It’s the density and repetition of several of them together, across a whole piece, that’s the actual signal, which is exactly what a proper statistical check measures instead of a reader guessing from a handful of examples.
Wherever this page describes a result: a detected mark is not proof of authorship, and an absent mark is not proof of human authorship. NeverPrompted's on-device rewrite can reduce detectable evidence but cannot guarantee defeating a vendor's undisclosed watermark, on any tier.