Most anti-slop-vision write-ups stop at the README: here is what the tool does, here is how you run it. This one covers what it refuses to do, and where it breaks.
Vision quality gates: prompt hygiene plus a VLM judge rubric with a SHIP / FIX / REGEN verdict — visual slop and hallucinations get cut before delivery.
In Russian: Vision-гейты качества: гигиена промпта плюс рубрика VLM-судьи с вердиктом SHIP / FIX / REGEN — визуальный слоп и галлюцинации отсекаются до отправки.
запуск: python3 scripts/eval.py img/ --prompt "a red guitar" -m <vision-model>
Python. MIT licensed. Standard library first: the tool reads the data you point it at and sends nothing anywhere.
Every rule in a checker like this can produce a false positive. Use it to find candidates for a rewrite, not to grade a writer, and not where the voice is the point.
Source, issue tracker and documentation: https://gitlab.com/ameobius-ai/anti-slop-vision
Other tools from the same author: https://ameobius-ai.gitlab.io