LLM Visibility Checker

How to read the result

This checker grades how easily a language model can extract a clear claim from the text you paste. It is a readability and structure measure, not a quality judgement — well-argued prose can score badly here, and that is useful information rather than a criticism.

Three things drive the number. Sentence length, because long compound sentences are harder to lift as a self-contained statement. Directness, meaning whether the passage states its point outright or builds to it. And concreteness — whether there is a checkable fact in there, or only assertion.

Use it on the opening paragraph of each section rather than a whole page. That is the unit an answer engine retrieves, and it is where a low score is worth acting on. A weak score on a narrative introduction is expected and usually fine; a weak score on the paragraph that answers your main heading is the one to rewrite.

The heuristics are English-language and run entirely on your device, so nothing you paste is transmitted. They approximate how a model reads; they do not query one, which is what keeps the tool free and private.

Rewriting a passage that scores badly

The fix is almost always structural rather than stylistic, and it is usually one of four moves. Put the answer in the first sentence instead of the third. Replace a pronoun that points at something in the previous paragraph with the noun itself. Split a sentence carrying two claims into two sentences carrying one each. Add the specific — the number, the threshold, the named standard — that turns an assertion into something checkable.

Restating the subject at the top of every section feels repetitive when you read the page straight through, and that instinct is what makes most well-written pages hard to quote. An answer engine never reads straight through: it retrieves one passage and discards the rest, so the repetition a human notices is exactly the context a model needs.