To make this approach work better, feed it a bunch of English text (or whatever language your document is in) before the document you really want to "spellcheck."
Essentially this isn't a spell "checker" so much as a spell "linter" — it looks for antipatterns statistically associated with bugs, and reports the patterns for further investigation.
If anyone knows where this trigraph-based "spellchecker" was first presented, I'd love to find out again.
LLMs have more stuff bolted onto them (embeddings, RLHF) but the autoregressive core is a direct descendent of that sort of language model.
I had a friend who wrote an article for the New York Times: the article made a lot of sense before she submitted it, but it was edited for length and style and it definitely read like a New York Times piece but didn't completely make sense.