Arguments

Create a Spotify playlist dynamically tuned to your current health/mood state, neurochemical optimization priorities, and work tempo.

Usage: /spotify-mood [optional override]

Examples:

• /spotify-mood - Auto-detect everything from data sources
• /spotify-mood focus - Override to deep work mode
• /spotify-mood recovery - Override to gentle recovery mode
• /spotify-mood energy - Override to high-energy boost

Arguments

$ARGUMENTS - Optional mood/mode override. If empty, auto-detect from data sources.

Data Sources

1. Health & Mood Data

Database: Read healthDatabase path from ~/.spotify-mood/config.json. If not configured, prompt the user to run /spotify-mood-setup.

The plugin expects a SQLite database with these tables:

health_metrics table (quantitative data):

Column	Type	Description
date	TEXT	ISO date
metric_type	TEXT	sleep_hours, hrv, caffeine, exercise_mins, steps, daylight_mins
value	REAL	Numeric value
unit	TEXT	hours, ms, mg, minutes, steps

daily_logs table (subjective data):

Column	Type	Description
date	TEXT	ISO date
mood_score	INTEGER	1-10 scale
energy_level	INTEGER	1-10 scale

Query current state:

-- Last night's sleep
SELECT value as sleep_hours FROM health_metrics
WHERE metric_type = 'sleep_hours' AND date >= date('now', '-1 day')
ORDER BY date DESC LIMIT 1;

-- Today's mood and energy
SELECT mood_score, energy_level FROM daily_logs
WHERE date = date('now') ORDER BY time DESC LIMIT 1;

-- Today's HRV (stress indicator)
SELECT AVG(value) as avg_hrv FROM health_metrics
WHERE metric_type = 'hrv' AND date = date('now');

-- Today's caffeine
SELECT value as caffeine_mg FROM health_metrics
WHERE metric_type = 'caffeine' AND date = date('now') LIMIT 1;

-- Today's exercise
SELECT value as exercise_mins FROM health_metrics
WHERE metric_type = 'exercise_mins' AND date = date('now') LIMIT 1;

2. Neurochemical Priorities

Read from ~/.spotify-mood/preferences.json (created by /feed-prefs):

• learning_weight (Acetylcholine) — focused, educational
• engagement_weight (Dopamine) — social, rewarding
• breakthrough_weight (Norepinephrine) — novel, surprising
• mood_weight (Serotonin/Endorphins) — uplifting, warm

3. Work Tempo

Run /work-tempo logic inline to determine current work context:

• Time of day and likely work phase
• Day of week (weekend vs. workday)
• Optional: user-provided calendar or task context

Mood-to-Music Mapping

Step 1: Calculate Composite State

sleep_factor = clamp(sleep_hours / 7.0, 0, 1.5)
energy_factor = clamp(energy_level / 10.0, 0, 1)
mood_factor = clamp(mood_score / 10.0, 0, 1)
stress_factor = 1.0 - clamp(avg_hrv / 60.0, 0, 1)  # Low HRV = high stress
caffeine_factor = clamp(caffeine_mg / 300.0, 0, 1)

Step 2: Determine Music Profile

Composite State	Profile	BPM Range	Energy	Valence
Low sleep + low mood	Recovery	60-90	Low	Warm
Low sleep + OK mood	Gentle Focus	70-100	Low-Med	Neutral
Good sleep + high energy	Power Mode	110-140	High	High
Good sleep + low energy	Activation	90-120	Med-High	Positive
High stress (low HRV)	Calm Down	50-80	Low	Warm
High caffeine + high energy	Channel It	120-150	High	Varied
Evening + any	Wind Down	50-85	Low	Warm
Weekend + good mood	Groove	100-130	Med	High

Step 3: Apply Neurochemical Weights

Weight Priority	Music Characteristics
High Learning (Acetylcholine)	Instrumental, ambient, minimal lyrics
High Engagement (Dopamine)	Familiar favorites, sing-along, rhythmic
High Breakthrough (Norepinephrine)	Eclectic, genre-crossing, unexpected
High Mood (Serotonin)	Warm, uplifting, major key, feel-good

Step 4: Generate Search Queries

Use genre pools from data/genre-pools.json to build 20-30 Spotify searches. Mix:

• Profile-matched genres and artists
• Neurochemical-modifier keywords
• Work-tempo adjustments (calmer for evening, energetic for morning)

Spotify Authentication

Read credentials from the user's .env file (path configured in ~/.spotify-mood/config.json):

• SPOTIFY_CLIENT_ID → set as SPOTIPY_CLIENT_ID
• SPOTIFY_CLIENT_SECRET → set as SPOTIPY_CLIENT_SECRET
• SPOTIFY_REDIRECT_URI → set as SPOTIPY_REDIRECT_URI

Token cache: ~/.spotify-mood/.spotify_cache

Requires Python package spotipy. If not available, install via:

uv pip install spotipy

Playlist Naming

Include detected state and date:

• "Monday Recovery Mode — Feb 17"
• "Deep Focus Tuesday AM"
• "Friday Evening Wind Down"
• "High Energy Saturday Groove"

Output

MOOD-AWARE PLAYLIST GENERATOR
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

HEALTH STATE
  Sleep:    6.2 hrs
  Mood:     7/10
  Energy:   6/10
  HRV:      42 ms (moderate stress)
  Caffeine: 100 mg

NEUROCHEMICAL WEIGHTS
  Learning:     0.25 | Engagement: 0.30
  Breakthrough: 0.25 | Mood:       0.20

WORK TEMPO
  Time: 2:30 PM (afternoon)
  Day:  Monday (work day)

MUSIC PROFILE: Gentle Focus + Mood Boost
  BPM: 70-100 | Energy: Low-Med | Valence: Warm-Positive

Creating playlist...
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Created: "Gentle Focus Monday PM — Feb 17" — 22 tracks
URL: https://open.spotify.com/playlist/...

Then open the playlist URL.

Low-Sleep Override

If sleep < 5 hours, automatically switch to Recovery profile regardless of other factors and display a gentle notice:

Note: Sleep was below 5 hours. Switching to Recovery mode.
Recovery playlists prioritize calm, restorative music.

Fallback Behavior

If health database is not configured or empty:

1. Use time-of-day heuristic only
2. Apply neurochemical weights from preferences
3. If no preferences exist either, ask the user how they're feeling