SlothTidy unveils frictionless, fully local AI daemon that auto‑organizes downloads while you sleep
llama privacy
| Source: Dev.to | Original article
SlothTidy, a fully offline AI file daemon, uses lightweight models via Ollama and llama.cpp to automatically classify, rename and organize files in the Downloads folder.
A new open‑source daemon called **SlothTidy** has been released to automate the sorting of files that accumulate in a user’s ~/Downloads folder. The tool watches the directory, runs tiny open‑weight models through Ollama and llama.cpp, and then classifies, renames and moves PDFs, screenshots and other documents—all without ever leaving the machine.
The project is positioned as a “zero‑friction, privacy‑first” solution for developers, students and anyone who feels overwhelmed by a growing download pile. By keeping inference local, SlothTidy sidesteps the data‑exfiltration concerns that have dogged many AI‑powered utilities, and it requires no manual tagging or scripting. The daemon was built for the Hacktoberfest 2026 “Slow and Steady” challenge, underscoring its ethos of steady, unobtrusive automation.
SlothTidy follows on the heels of **SlothDesk**, the local‑first AI downloads organizer we covered earlier this week. Together the tools illustrate a growing niche of privacy‑centric AI utilities that aim to replace cloud‑based services with on‑device processing. For users who have grown wary of sending personal files to remote APIs, the ability to tidy a filesystem automatically while the computer is idle could be a compelling alternative to manual sorting or generic rule‑based scripts.
The next steps to watch include community contributions on the GitHub repository, potential integrations with other local‑first workflows (such as the markdown auto‑commit daemon from the same author), and whether the approach gains traction beyond hobbyist circles. If adoption expands, SlothTidy could become a reference point for how lightweight, offline AI can handle everyday productivity chores without compromising privacy.
Sources
Back to AIPULSEN