HermesBELARABI
العربيةSearch/CheckingSign in
AcademyDirectorySolutionsStudioProjectsCompareSearch Releases Pricing Account Sign in
Directory → SKILL
SKILLbundledHermes Bundled Skills

Songsee

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

AudioVisualizationSpectrogramMusicAnalysisBundledHermes skill
Last registry verification2026-08-18v1.0.0community
Open original source ↗اقرأ بالعربية
Plain meaning

What does it add to Hermes?

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

Songsee is a skill related to design and media. It adds tools to create, read, or modify media such as designs, images, audio, or video.

This plain-language explanation is based on the publisher description. The original text remains visible for verification.

Use it when

Use it when your goal in design and media is clear and you can limit it to the data and actions it actually needs.

Skip it when

Do not add it merely to experiment when Hermes already has a simpler path, or when you cannot review its source and permissions.

Who is it for?

Best for users who want a repeatable way of working inside Hermes.

Safe first test

Start with a disposable asset and create a copy instead of changing the original.

Original publisher description

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

✓
Data source

This entry was indexed from Hermes Bundled Skills. Our explanation interprets the type and domain without inventing a capability not present upstream.

!
Security review

The source is official or editorially reviewed, but you still need to review permissions and version compatibility.

Safe setup path

Inspect, install, then test.

  1. 01
    Open the source

    Match the publisher, license, and description to your need. Check the real update history.

  2. 02
    Review permissions and secrets

    Never paste a secret value into this site. Use environment-variable names and grant the smallest scope.

  3. 03
    Copy setup only after review

    The controls below copy text. They do not execute commands on your device.

  4. 04
    Test with a non-sensitive task

    Inspect the visible tools, then exclude write or delete tools you do not need.

Setup method

Already installed with Hermes.

This skill ships with Hermes and loads when the agent decides it is relevant. There is nothing to install; read the definition below so you know what it will do.

Open the official page ↗
The full skill definition

Exactly what Hermes loads when this skill runs.

Reproduced from the official documentation. Read it before enabling the skill: this text becomes the agent's instructions.

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

Skill metadata

A lookup table. Do not read it all; find the row that applies to you.

SourceBundled (installed by default)
Pathskills/media/songsee
Version1.0.0
Authorcommunity
LicenseMIT
Platformslinux, macos, windows
TagsAudio, Visualization, Spectrogram, Music, Analysis

Reference: full SKILL.md

Explains the idea itself. Read it slowly; the later sections build on it.

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

Prerequisites

Explains the idea itself. Read it slowly; the later sections build on it.

Requires Go ↗:

Shell1 line
go install github.com/steipete/songsee/cmd/songsee@latest

Optional: ffmpeg for formats beyond WAV/MP3.

Quick Start

Ordered, practical steps. Run one and confirm it worked before moving on.

Shell14 lines
# 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

A lookup table. Do not read it all; find the row that applies to you.

Use --viz with comma-separated values:

TypeDescription
spectrogramStandard frequency spectrogram
melMel-scaled spectrogram
chromaPitch class distribution
hpssHarmonic/percussive separation
selfsimSelf-similarity matrix
loudnessLoudness over time
tempogramTempo estimation
mfccMel-frequency cepstral coefficients
fluxSpectral flux (onset detection)

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

Common Flags

A lookup table. Do not read it all; find the row that applies to you.

FlagDescription
--vizVisualization types (comma-separated)
--styleColor palette: classic, magma, inferno, viridis, gray
--width / --heightOutput image dimensions
--window / --hopFFT window and hop size
--min-freq / --max-freqFrequency range filter
--start / --durationTime slice of the audio
--formatOutput format: jpg or png
-oOutput file path

Notes

Explains the idea itself. Read it slowly; the later sections build on it.

  • 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