About this skill

Problem

Directories get messy fast: PDFs, images, old project files, and temporary exports all land in the same place. Moving files by hand is error-prone and hard to repeat. This skill turns archiving into a rule-based Python workflow, making it useful for Downloads folders, project roots, or backup directories where the same organization steps need to run again.

How It Works

Rule configuration: pattern supports fnmatch expressions such as *.pdf, report_*, readme.txt, and *. Files match the first rule in order.
Safe preview: run a dry run first to inspect what would be moved or copied before touching the source tree.
Move or copy: supports moving files to a destination, or preserving originals with copy mode. use_date_folder can create YYYY-MM-DD subfolders.
Structure preservation: preserve_structure keeps relative paths, for example /data/projects/alpha/report.pdf becomes ./archive/projects/alpha/report.pdf.

Limits

This is a filename- and extension-based archiver, not a semantic or full-text organizer. The catch-all * should usually be last. Paths with spaces need quoting, and rule order matters. It relies on the Python standard library for cross-platform file operations, but users still need to verify permissions, sync-tool behavior, and the consequences of move actions.

Screenshots

Use Cases

Use a Downloads folder as a staging area, sorting `*.pdf` files, images, and other files into separate directories after a dry-run preview.
Clean an old project directory by copying dated or named files into an archive folder while preserving the original relative structure.
Organize delivery materials by moving `report_*` files and known filenames into a project archive path under `YYYY-MM-DD` folders.
Back up exported documents in batches by matching document types and copying them to backup storage without deleting source files.

Best For

Engineers maintaining local document trees who want scattered PDFs, images, and old files archived by explicit rules.
Project assistants preparing delivery packages who want `report_*` files and named assets moved into dated archive folders.
Ops engineers handling cross-platform file migration who want to validate pattern matches and destination paths with a dry run before moving files.
Python developers maintaining backup scripts who want to wrap `shutil` move/copy, structure preservation, and Unicode filename handling into a reusable workflow.