A FOSS app maintainer did something most people only talk about: they went through every one of the 102 apps pushed in F-Droid's September 12 update cycle, opened each code repository, and rated it by degree of AI involvement. The result is not surprising, but more extreme than expected: 74 apps (72.5%) were judged mostly AI-written, only 18 (17.6%) showed little to no signs of AI involvement, and 10 (9.8%) were hard to categorize.
The method: no detector, just "smells"
The author admits upfront that text does not carry enough meta-information for accurate detection — nobody can build a real "slop detector". The workaround is a rough three-tier system — "Mostly AI / Hard to say / No signs of AI" — based on recent commits, repository aesthetics and project branding: whether the README was lazily generated, whether code review was delegated back to the LLM itself, and whether the repo carries agentic infrastructure like Claude Code or Codex. Any repository with agentic infrastructure automatically lands in the "Mostly AI" tier, on the grounds that the author does not believe it is possible to use AI responsibly from within a coding harness. Ratings look only at recent commits, not project history: a long-lived app whose recent commits read as LLM-authored still counts as "mostly AI". The author also concedes the judgments may contain errors, and explicitly did not do any code quality analysis.
Beyond the headline number, sharper details
Of the 5 apps hosted on Codeberg, 4 were judged mostly AI-generated — and Codeberg has already announced an AI policy banning such apps, though cleanup clearly takes time. One user, brandonp2412, maintained several apps in this update cycle, all entirely vibe-coded, scattered across unrelated namespaces like com.presley.* and com.codesail.*; the author's guess is either a very avid vibe-coder, or an agent that was somehow given a GitHub account. Well-known projects appear on the list too: Yubico Authenticator was rated "Mostly AI", while the official Wikipedia app landed in "Mostly Human" — most commits look human-made, but there is quite a lot of Claude infrastructure in the repo, which surprised the author as well. There is also a pair of apps branded with the "Don't tread on me" flag that have been in development for a long time, yet every change was made through the GitHub web file editor — no git at all.
The latest cell in the "measure the AI share" lineage
Placed in a larger frame, this audit is the newest data point in a lineage of quantifying how much of a content ecosystem is AI-made: Pew Research Center previously sampled and found that more than a third of English webpages published after ChatGPT's release show AI writing traces; studies of biomedical paper repositories put the share even higher. Web pages, papers, and now Android open-source app code — three different ecosystems, converging magnitudes. What makes this one different is that the object is code: code has compilers and runtimes as a backstop, so "AI-written" does not directly equal "unusable" in an app store context. The author keeps that clarity too — acknowledging LLMs are incredibly useful, and that after the audit, several FOSS apps they personally use also showed heavy LLM usage: "I'll still use them, as I find them useful, but this whole experiment has left me feeling quite conflicted."
So what
The real value of this audit is not the 72.5% figure itself, but that it turns a vibes-only question into a discussable public fact. For community infrastructure like F-Droid and Codeberg, writing a policy is one thing; whether the review pipeline can digest this ratio is another. For developers, a cheap legitimate path already exists: at least one app on the list (Bati) discloses its AI involvement right in the README, which the author tagged "Thanks for making it easy" — disclosure is the cheapest trust signal available. For users, the "open source" label is quietly downgrading: it used to imply "human-written, auditable"; now it only promises "source visible". Source visible, and someone answerable for it, are two different things.
Reference: original analysis at tintotint.eu (https://tintotint.eu/whacky-corner/f-droid_slop/); Solidot coverage (https://www.solidot.org/story?sid=85385)