For writing, it checks known vocab and punctuation tells, as well as subtler tells related to cadence, and assigns it a score subject to an adjustable threshold. If the text fails, users have the option to flag offending text, hide it, or block the page entirely (with the option to see anyway).
For media, it's admittedly fairly weak, as it relies on C2PA metadata which is stripped from all of the social media sites where it would be most helpful. (Anyone else have chronically online boomer parents continually gobbling up slop like it's real information?)
I have a D-slop+ version in the works that should be able to handle the media itself, but it's going to have to make API calls to have real teeth, which means I can't offer it for free. If this extension validates the concept, I'm happy to build it for y'all.
Yes, I vibe-coded it, but an ancillary bonus to the project accrued when it inspired me to cook dinner listening to Metallica's "Fight Fire with Fire," which in turn brought my 5 y/o running into the kitchen with every musical instrument in the house for an impromptu karaoke speed metal session.
It's MIT license open-source, full brief at https://github.com/jared-the-automator/d-slop; This forum is full of people smarter than me, so I'm open to suggestions.
HerbManic•2h ago
The limit ultimately will be how well the algorithm can keep up with changes in LLM cadence over time. This is usually were project like this come undone, the concept it easy enough to build, it is the up to date data set where the real magic is.
But other than that, very cool to see and interested to see how it goes.