Install
openclaw skills install music-discoveryRecommend music tracks and playlists tailored to mood, activity, BPM, energy, or genre using Spotify and Last.fm data.
openclaw skills install music-discoveryHelps listeners find tracks and playlists that fit a mood, activity, or taste profile—study, commute, workout, sleep, or “something like this artist.” Use when the user wants personalized picks, scene-based sets, or exploration without manual crate-digging.
Trigger keywords: music recommendation, playlist, mood, BPM, study music, workout, discover similar artists
pip install requests spotipy
references/music_discovery_guide.md).| Command | Description | Example |
|---|---|---|
recommend | Recommend tracks | python3 scripts/skills/music-discovery/scripts/music_discovery_tool.py recommend [args] |
playlist | Build a playlist concept | python3 scripts/skills/music-discovery/scripts/music_discovery_tool.py playlist [args] |
mood | Recommend by mood | python3 scripts/skills/music-discovery/scripts/music_discovery_tool.py mood [args] |
python3 scripts/skills/music-discovery/scripts/music_discovery_tool.py recommend --scene office --mood relaxed
python3 scripts/skills/music-discovery/scripts/music_discovery_tool.py playlist --scene workout --bpm 140
python3 scripts/skills/music-discovery/scripts/music_discovery_tool.py mood --feeling happy
# Music Discovery report
**Generated**: YYYY-MM-DD HH:MM
## Key picks
1. [Track / artist — one-line why]
2. …
3. …
## Snapshot
| Title | Artist | Why it fits |
|-------|--------|---------------|
## Playlist sketch (optional)
- **Theme**: …
- **Tempo / energy**: …
- **Avoid**: …
## Notes
[Ground claims in API or user-stated taste—no invented chart positions.]