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/songsee

Generate spectrograms and audio feature visualizations (mel, chroma, MFCC, tempogram, etc.) from audio files via CLI. Useful for audio analysis, music production debugging, and visual documentation.

From plugin
zorro-agent
1078 skills

Claude Code

$ npx -y skills add braxtonROSE4/zorro-agent --skill songsee --agent claude-code

SKILL.md

songsee.SKILL.md
name: songsee
description: Generate spectrograms and audio feature visualizations (mel, chroma, MFCC, tempogram, etc.) from audio files via CLI. Useful for audio analysis, music production debugging, and visual documentation.
version: 1.0.0
author: community
license: MIT
metadata:
  zorro:
    tags: [Audio, Visualization, Spectrogram, Music, Analysis]
    homepage: https://github.com/steipete/songsee
prerequisites:
  commands: [songsee]

songsee

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

Prerequisites

Requires [Go](https://go.dev/doc/install):

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:

| Type | Description | |------|-------------| | `spectrogram` | Standard frequency spectrogram | | `mel` | Mel-scaled spectrogram | | `chroma` | Pitch class distribution | | `hpss` | Harmonic/percussive separation | | `selfsim` | Self-similarity matrix | | `loudness` | Loudness over time | | `tempogram` | Tempo estimation | | `mfcc` | Mel-frequency cepstral coefficients | | `flux` | Spectral flux (onset detection) |

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

Common Flags

| Flag | Description | |------|-------------| | `--viz` | Visualization types (comma-separated) | | `--style` | Color palette: `classic`, `magma`, `inferno`, `viridis`, `gray` | | `--width` / `--height` | Output image dimensions | | `--window` / `--hop` | FFT window and hop size | | `--min-freq` / `--max-freq` | Frequency range filter | | `--start` / `--duration` | Time slice of the audio | | `--format` | Output format: `jpg` or `png` | | `-o` | Output file path |

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
Read more
@braxtonrose4
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Questions about songsee.

Which coding agents can use songsee?
songsee installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.