What happens if the album doesn't exist yet?

The skill will return an error and suggest using the /new-album skill to create the directory structure before importing art.

Does it support formats other than JPG and PNG?

It supports .jpg, .jpeg, .png, and .webp. If you try to import a different file type, the skill will issue a warning and ask for confirmation before proceeding.

Where does the skill save the imported album art?

The skill saves the art in two places: the audio folder (renamed to album.png for distribution) and the content folder (using the original file extension for documentation).

Does this skill require a specific configuration?

Yes, it requires a config.yaml file located at ~/.bitwize-music/ containing your content_root, audio_root, and artist name.

Music Album Art Importer

Name: Music Album Art Importer
Author: bitwize-music-studio

bybitwize-music-studio

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Productivity & Workflow

Automates the distribution and naming of album artwork across audio production and documentation directories.

About

The Import Art skill streamlines music production workflows by ensuring album artwork is correctly placed for both distribution and archival purposes. It reads local Bitwize Music configuration files to identify artist paths and automatically detects album genres to find the correct destination. By handling dual-location copying—specifically naming files for streaming platform compatibility in audio folders while preserving original metadata in content folders—this skill eliminates manual file management errors in Human + AI music production pipelines.

Key Features

Dual-destination file distribution for audio and documentation folders
Automatic genre detection via directory traversal
YAML configuration integration for personalized path mapping
Validation checks for source files, image types, and album existence
Standardized renaming for platform-specific compatibility (album.png)
3 GitHub stars

Use Cases

Preparing music releases for mastering and digital distribution
Automating asset management during high-volume music production
Organizing visual assets within a structured Suno-AI music repository

About

Key Features

Dual-destination file distribution for audio and documentation folders
Automatic genre detection via directory traversal
YAML configuration integration for personalized path mapping
Validation checks for source files, image types, and album existence
Standardized renaming for platform-specific compatibility (album.png)
3 GitHub stars

Use Cases

Preparing music releases for mastering and digital distribution
Automating asset management during high-volume music production
Organizing visual assets within a structured Suno-AI music repository