Flag ai-sounding text

A freelance content writer submits a draft to a client who explicitly wants human-written copy, and the client runs it through their own AI checker before paying — a check the freelancer has no visibility into until the invoice is already disputed. Running a draft through a detector before sending it over, as an internal QA signal, at least means no unpleasant surprise arrives after the fact.

This estimates the likelihood a piece of text reads as AI-generated and highlights the specific sentences driving that score, offered purely as an internal signal before publishing somewhere that expects human writing. It makes no claim about how it would perform against any specific external platform's own detector — those are separate systems this tool has no visibility into or control over.

No AI detector is fully accurate, and this isn't a minor caveat specific to this tool — it's a known, industry-wide limitation, and both false positives (flagging human-written text as AI-generated) and false negatives (missing text that was AI-generated) happen regularly across every detector on the market. A writer whose style is clean and consistent can score as more "AI-like" than someone writing messier, purely because detectors key on patterns like sentence-length consistency that don't perfectly track who wrote something.

This is exactly why the score here is deliberately framed as an internal QA signal, not a claim about accuracy against any other platform's own checker. A specific external platform — an academic institution's plagiarism system, a client's procurement tool — runs its own detector with its own methodology, and a result here says nothing certain about what that separate system would report on the same text; treating a good score here as guaranteed to pass some other system's check is a real overreach.

Given this genuine unreliability, the responsible way to use this feature is as one input among several judgment calls, not a gate deciding whether a piece gets used at all. A flagged high score is worth a look at the highlighted sentences and a human read for anything stiff or formulaic, but a low score isn't proof the text will satisfy every external check it might later face, and neither result should be treated as more certain than the honest state of AI-detection technology supports.