AI Tell Highlighter

The scan checks more than 70 patterns in four families. Overused transitions — furthermore, moreover, additionally, firstly — are the classic glue language models lean on to stitch ideas together. Clichés and buzzwords like delve, unlock, game-changer and cutting-edge appear in AI output far more often than in human drafts. Hedgy qualifiers (“it’s worth noting that,” “arguably,” “tends to”) soften every claim the way a model hedging its bets does. And structural habits — em-dash chains, triple-item lists, “not only X but also Y” constructions — give prose that unmistakable generated rhythm. Each highlight links to a card explaining why the pattern reads as AI-ish, plus when it is perfectly fine to keep.

Take a 182-word product announcement draft. The scan finds 16 highlights: 7 transitions (moreover twice, furthermore, additionally, in conclusion, firstly, lastly), 4 clichés (delve, unlock, game-changer, cutting-edge), 3 qualifiers (“it’s important to note,” arguably, tends to) and 2 structural habits (a triple list, an em-dash chain). That is roughly one highlight every 11 words — a density where readers start hearing the “AI voice” even in human-written text.

Revision takes ten minutes: moreover and furthermore become specific connectors (“because,” “for example”), delve becomes “explore,” the triple list becomes two crisp sentences. The result keeps 4 deliberate highlights — a 75% drop — and reads like a person with opinions instead of a model with templates.

This is a style editor, not an AI detector: it flags patterns, it cannot tell you who wrote a text, and a highlighted phrase proves nothing about authorship. The catalog is English-only. Very short texts under about 20 words give unreliable results because there is not enough prose to judge. And it does not understand context — a “moreover” in a legal brief may be exactly right, which is why every highlight is a suggestion to reconsider, never a verdict.