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songsee

Turn audio into spectrograms, images showing frequencies over time, and panels of features such as loudness and rhythm. Combine views in a grid and choose a time segment, color palette, and output image size.

OriginalShow the original description

Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.

AI rating100/ 100See how to install

Good for

  • Viewing audio frequencies over time
  • Comparing loudness and rhythm in a panel grid
  • Visualizing a selected audio segment
  • Exporting audio visualizations as PNG or JPG

Overview

What it does

songsee creates images from audio files, including spectrograms that show how frequencies change over time and panels that represent loudness, rhythm, and other features. Use its commands to choose which views to display and arrange multiple views in a grid. You can set the color palette, image dimensions, frequency range, and level of analysis detail, then save the result as JPG or PNG.

When it helps

Use it to examine audio visually or look at the same recording from several perspectives. You can specify a start time and duration to visualize a particular passage as well as an entire track. The material also describes how to supply audio through standard input.

Example requests

  • “Create a spectrogram of track.mp3.”
  • “Make an image with panels showing loudness, rhythm, and other features.”
  • “Visualize eight seconds starting at 12.5 seconds and save it as slice.jpg.”

Notes

The songsee command-line tool is required. The material provides a Homebrew installation method. WAV and MP3 files are read directly; other formats use ffmpeg when it is available.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodThe material explicitly describes generating spectrograms and feature panels from audio.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
AGoodExamples cover basic commands, time slices, standard input, and output image formats.
SafetyAre sending data, deleting files, and running commands disclosed?
AGoodCommands read audio and write images; no deletion or external transmission is described.
Easy setupDoes it need few tools or API keys, and are they documented?
AGoodHomebrew installation configuration for songsee and conditions for using ffmpeg with other formats are specified.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 19, 2026. Treat it as a guide and read the original before installing.

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Files included (1)

  • SKILL.md1.3 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

songsee

Generate spectrograms + feature panels from audio.

Quick start

  • Spectrogram: songsee track.mp3
  • Multi-panel: songsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux
  • Time slice: songsee track.mp3 --start 12.5 --duration 8 -o slice.jpg
  • Stdin: cat track.mp3 | songsee - --format png -o out.png

Common flags

  • --viz list (repeatable or comma-separated)
  • --style palette (classic, magma, inferno, viridis, gray)
  • --width / --height output size
  • --window / --hop FFT settings
  • --min-freq / --max-freq frequency range
  • --start / --duration time slice
  • --format jpg|png

Notes

  • WAV/MP3 decode native; other formats use ffmpeg if available.
  • Multiple --viz renders a grid.

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