songsee

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

202|36|Updated Jan 27, 2026
One-click install
npx skills add https://github.com/adoresever/AGI_Ananas --skill songsee-adoresever
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/adoresever/AGI_Ananas/tree/main/26.2.21openclaw-viking/skills/songsee
Command: npx skills add https://github.com/adoresever/AGI_Ananas --skill songsee-adoresever

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Audio researchers and producers often need quick, visual representations of sound without manual, error-prone plotting workflows. This skill provides an accessible CLI to generate spectrograms and feature panels from audio data, streamlining analysis and presentation.

Core Features & Use Cases

  • Generate spectrograms and feature-panel visualizations from audio inputs.
  • Create time-sliced views and multi-panel layouts to compare different features and styles.
  • Supports configurable options such as start/duration, windowing, and color palettes for flexible analysis and reporting.

Quick Start

Run songsee on an audio file to generate a spectrogram and multi-panel visualizations.

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 using the command line?

To generate a spectrogram from an audio file, use the songsee CLI by providing a direct file path or streaming piped data. It quickly creates visual representations for exploratory analysis across tracks or datasets.

What is a feature-panel visualization for audio analysis?

A feature-panel visualization displays multiple audio characteristics simultaneously using multi-panel layouts. songsee generates these views to help researchers and producers compare different sound features and styles without manual plotting workflows.

Does the songsee CLI support piping streaming audio data for quick visualization?

Yes, the songsee CLI supports streaming piped data inputs alongside direct file paths. This allows users to generate spectrograms and feature panels dynamically during audio processing workflows.

Can I customize spectrogram color palettes and time-slicing options?

You can customize spectrograms with configurable options including start and duration time-slicing, windowing, and color palettes. These style presets enable flexible audio analysis and reporting.

Do I need to install any dependencies to use the songsee CLI?

You need the songsee binary installed to use this skill. The binary supports installation via brew, providing an accessible command-line interface for generating audio visualizations.