title: “Songsee — Audio spectrograms/features (mel, chroma, MFCC) via CLI” sidebar_label: “Songsee” description: “Audio spectrograms/features (mel, chroma, MFCC) via CLI”

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Songsee

Audio spectrograms/features (mel, chroma, MFCC) via CLI.

Skill metadata

Reference: full SKILL.md

:::info The following is the complete skill definition that Hermes loads when this skill is triggered. This is what the agent sees as instructions when the skill is active.

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songsee

Generate spectrograms and multi-panel audio feature visualizations from audio files.

Prerequisites

Requires Go:

go install github.com/steipete/songsee/cmd/songsee@latest

Optional: ffmpeg for formats beyond WAV/MP3.

Quick Start

# Basic spectrogram
songsee track.mp3

# Save to specific file
songsee track.mp3 -o spectrogram.png

# Multi-panel visualization grid
songsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux

# Time slice (start at 12.5s, 8s duration)
songsee track.mp3 --start 12.5 --duration 8 -o slice.jpg

# From stdin
cat track.mp3 | songsee - --format png -o out.png

Visualization Types

Use --viz with comma-separated values:

Multiple --viz types render as a grid in a single image.

Common Flags

Notes

• WAV and MP3 are decoded natively; other formats require ffmpeg
• Output images can be inspected with vision_analyze for automated audio analysis
• Useful for comparing audio outputs, debugging synthesis, or documenting audio processing pipelines