I want to use Claude Code to help organize several terabytes of audio, but the folders are messy because they’ve come from lots of different sources/versions. The folder names are inconsistent, deeply nested, and not cleanly structured by artist, album, category, etc. One slower approach I was trying was generating logs of the current folder/file names with a Python script, with discographies written in a .md file and manually approve Claude’s suggestions bit by bit. But because the collection is so large, it’s taking a long time. What I’d like to test is an agentic workflow on a copied version of the hard drive, not the original. Ideally, Claude Code would recursively scan the entire folder tree, understand the files and metadata, suggest a new structure, and then organize the music into categories, artists, albums, or other sensible groupings. The issue is that the folders are very deep, and Claude Code only sees a limited amount unless I use scripts to expose the structure. So I’m wondering: What’s the most optimized way to let Claude Code inspect and organize a huge, deeply nested music/audio library? Should I use Python scripts to generate manifests, metadata summaries, and dry-run move plans? Are there better tools, MCP connectors, or workflows that I can use for Claude Basically, I want to test the maximum practical capability of Claude Code for organizing a massive, messy audio archive. Has anyone tried something like this, and what workflow would you recommend? Note: I’m good at promoting and such, I just need suggestions on the best way to go about it submitted by /u/Nano-Watch
Originally posted by u/Nano-Watch on r/ClaudeCode