A student eyeballed 102 F-Droid apps for LLM slop. The method is the story.
Someone on tintotint.eu went through every app in the September 12, 2026 F-Droid update batch, 102 apps, and classified each one by how likely it is that an LLM wrote it. Mostly AI, hard to say, no signs of AI. One student, one batch, a few tiers, done. The results are less interesting than the method, because the method is the honest part. Here's how they classified: no slop detector, no code…
A student evaluated 102 apps from the September 12, 2026 F-Droid update batch to determine the likelihood of AI-generated code. The classification was based on repo aesthetics, commit tone, emoji density in the README, presence of AI infrastructure, and AI disclosure lines in the README. However, the method has limitations, as it's difficult to determine if code was AI-authored even when reviewing the full repository with its history and branding.
The survey suggests that provenance is not resolvable, and the idea of gating review on AI code is a dead end. Instead, focus on reviewing the code itself, regardless of the author. Key factors to consider include the impact on authentication, error handling, and the presence of new dependencies with tags.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
