awnist

There is a one shot rewrite function now, but you're right, even when asking the LLM avoid some of the patterns, it will stubbornly repeat them. It's a bit more reliable with smaller fragments of text.

Good idea, I did test on HN op/ed submissions and likely upgraded my own wetware slop radar in the process

That's right, its tokenization and fragment rules use fairly simple heuristics that assume whitespace delimited words plus English language/punctuation. Proper CJK support would require language specific tokenization and morphological parsing. Correcting rules like "≤4 words = dramatic fragment" would be difficult. The more complex rules already require LLM roundtrips, so supporting all languages in one pass would need to rely on LLM alone, I imagine.

Which brings up an interesting point - what do these LLM clichés look like in Japanese?

https://github.com/awnist/slop-cop#client-side-instant

Good idea! Nothing special about the Anthropic calls, would be simple to point at local models

It isn’t an AI detector. It flags valid language patterns that have become LLM-output clichés through overuse. False positives are a given.

and I'll never give up on em dashes

Run it locally, Github is linked on the bottom left:

https://github.com/awnist/slop-cop

True. This is just an LLM cliché detector, highlighting stylistic habits they're currently prone to. You'll start noticing them everywhere when you internalize the patterns.