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music-emotion

Original：🇺🇸 English

Translated

Analyze emotion — mood classification, energy, valence, genre detection

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Sourcebenzema216/dreamina-claude-skills

Added on2026-02-07

NPX Install

npx skill4agent add benzema216/dreamina-claude-skills music-emotion

Tags

Translated version includes tags in frontmatter

music-emotion-analysis clap-model audio-classification mood-detection genre-recognition

SKILL.md Content

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/music-emotion — Emotion & Style Analysis

Classify the emotional content of an audio file: primary mood, energy level, emotional valence, arousal, genre, and mood tags.

Usage

/music-emotion <audio_file_path>

Steps

Validate the audio file path
Run emotion analysis:

bash

python3 -m music_analyzer emotion "<audio_file_path>"

Present results:
- Primary Emotion: Dominant mood (happy, sad, calm, energetic, etc.)
- Energy Level: 0-1 scale with curve across song segments
- Valence: -1 (negative) to 1 (positive)
- Genre: Detected genre
- Mood Tags: Descriptive mood keywords

Detection Methods

CLAP (full tier): AI-based emotion/genre classification using CLAP model
Heuristic (lite tier): Spectral features + rhythm + tonality-based rules

The method used is noted in the

method

field of the output.

Output Fields

Field	Description
`primary_emotion`	Dominant emotion label
`secondary_emotions`	Additional emotion tags
`overall_energy`	Energy level 0-1
`energy_curve`	Energy values per segment
`valence`	Emotional valence -1 to 1
`arousal`	Arousal level 0-1
`genre`	Detected genre
`mood_tags`	Mood descriptor keywords