Sloth Tidy: A Local AI That Cleans Your Messy Folders While You Nap
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady What I Built Sloth Tidy is a command-line tool that cleans up a messy folder (think Downloads) using an open-weight model running on my own machine. You point it at a folder. For each file it reads a short s
Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady Submission 🦥
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady
Sloth Tidy is a command-line tool that cleans up a messy folder (think Downloads) using an open-weight model running on my own machine.
You point it at a folder. For each file it reads a short snippet, then proposes a category, a clean filename, and a destination: scan0012.pdf becomes Invoices/2026/2026-10-31_meralco-electricity-bill.pdf. Nothing moves until you review a dry-run plan and apply it, and every move can be undone with one command. There's also a watch mode that files new arrivals in the background.
It's for anyone who has a folder full of scan0012.pdf, Document (3).docx, and Screenshot 2026-10-03.png and keeps putting off the cleanup. The sloth move is to run it once and walk away.
Point it at a messy folder; a local open-weight model proposes where everything belongs.
Sloth Tidy sends readable file snippets to Ollama on your machine by default. After you pull a model, it can run without internet access, hosted model APIs, or API keys; file contents stay on your machine. Choose another Ollama model with SLOTH_MODEL, and steer its decisions with rules.yaml. A remote Ollama server is possible only when you explicitly pass --allow-remote.
ollama pull qwen2.5:7b npm install npm run build npm test Enter fullscreen mode Exit fullscreen mode Quick start with the demo Generate the 30-file demo, copy it, and plan against the copy. The plan is written beside the copy so it is not…