In this article, I propose a definition of software slop based on human attention (slop = code that hasn't been reviewed or verified) and sketch out a way to estimate how "sloppy" a piece of software is. I put it to the test with Slop-O-Meter, an experimental tool that analyzes public GitHub repos and assigns them a sloppiness score. I then discuss the results of the tool, which are not very reliable, but interesting nonetheless.