From spotify-mood
Customize your neurochemical optimization weights for mood-aware playlist generation.
How this skill is triggered — by the user, by Claude, or both
Slash command
/spotify-mood:feed-prefsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Customize your neurochemical optimization weights for mood-aware playlist generation.
Customize your neurochemical optimization weights for mood-aware playlist generation.
Usage: /feed-prefs [option]
Examples:
$ARGUMENTS - Optional: --show, --reset, or --preset NAME
YOUR NEUROCHEMICAL WEIGHTS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Learning (Acetylcholine) ████████░░░░░░░░ 0.25
Instrumental, ambient, focus music
Engagement (Dopamine) ██████████░░░░░░ 0.30
Familiar favorites, rhythmic, sing-along
Breakthrough (Norepinephrine) ████████░░░░░░░░ 0.25
Eclectic, genre-crossing, unexpected
Mood (Serotonin/Endorphins) ██████░░░░░░░░░░ 0.20
Uplifting, warm, feel-good
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
| Preset | Learn | Engage | Break | Mood | Best For |
|---|---|---|---|---|---|
balanced | 0.25 | 0.30 | 0.25 | 0.20 | General use |
scholar | 0.40 | 0.15 | 0.30 | 0.15 | Deep focus, study |
social | 0.15 | 0.45 | 0.20 | 0.20 | Background social |
creative | 0.20 | 0.20 | 0.40 | 0.20 | Breakthrough focus |
uplifting | 0.15 | 0.25 | 0.20 | 0.40 | Mood boost |
If no arguments, show current weights and ask what to adjust. Weights must sum to 1.0.
Write to ~/.spotify-mood/preferences.json:
{
"weights": {
"learning": 0.25,
"engagement": 0.30,
"breakthrough": 0.25,
"mood": 0.20
},
"updated_at": "ISO timestamp"
}
Also reads from ~/.claude-social-feed/preferences.json if it exists (for users who also have the agentic-social-feed plugin installed), using those weights as defaults.
npx claudepluginhub fredzannarbor/spotify-mood-pluginResets music preferences (genre, volume, favorites) to default values. Part of the claude-music plugin, invoked via slash command.
Generates personalized music playlists by analyzing listening history from Apple Music, Spotify exports, or manual input. Creates taste profiles, generates songs and album covers via mmx CLI, and plays them back.
Plays curated music presets across mood, genre, and activity categories via MCP tool. Useful for setting a coding or study atmosphere.