songsee

Generate spectrograms and audio feature visualizations from audio files.

1|Updated Mar 22, 2026
One-click install
npx skills add https://github.com/nelohenriq/hermes-agent-plus --skill songsee-nelohenriq
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/nelohenriq/hermes-agent-plus/tree/main/skills/media/songsee
Command: npx skills add https://github.com/nelohenriq/hermes-agent-plus --skill songsee-nelohenriq

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manually generating audio visualizations from raw audio files is time-consuming and requires multiple tools; SongSee provides a CLI to produce standardized spectrograms and feature plots in one step.

Core Features & Use Cases

  • Generate spectrograms, mel spectrograms, chroma, MFCCs, and tempograms from audio inputs.
  • Create multi-panel visualizations for documentation, music analysis, or debugging audio pipelines.

Quick Start

Generate a multi-panel visualization from an audio file using the songsee CLI to output a PNG.

Frequently Asked Questions about songsee

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a spectrogram from an audio file for visual documentation?

You can generate a spectrogram from an audio file by using a CLI tool to produce a standardized PNG image in one step. This simplifies creating multi-panel visualizations for music analysis or debugging audio pipelines.

What audio feature visualizations can I create for music production debugging?

For music production debugging, you can create visualizations including mel spectrograms, chroma, MFCCs, tempograms, loudness, and spectral flux. These features help analyze audio characteristics and identify pipeline issues.

Do I need to install Go to use a CLI tool for audio analysis?

Yes, you need Go installed as a prerequisite to install and run the songsee CLI. This allows you to execute commands that generate spectrograms and other audio feature plots locally.

What is the best way to visualize MFCCs and chroma features from raw audio?

The best way to visualize MFCCs and chroma features is using a single CLI tool that processes raw audio files and outputs standardized multi-panel plots, eliminating the need for multiple separate visualization tools.

Can I create multi-panel audio visualizations in one step?

Yes, you can create multi-panel audio visualizations in one step by running a CLI command on your audio input. This generates a comprehensive PNG image containing spectrograms and various feature plots for documentation.