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songsee

Generate spectrograms and audio feature visualizations from audio files via CLI.

1|Updated Feb 17, 2026
Search Tags:#cli#visualization#music#Chroma#spectrogram#mfcc#audio analysis
One-click install
npx skills add https://github.com/brittb-dev/zerogravityclaw --skill songsee-brittb-dev
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/brittb-dev/zerogravityclaw/tree/main/src/hermes-core/skills/media/songsee
Command: npx skills add https://github.com/brittb-dev/zerogravityclaw --skill songsee-brittb-dev

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Audio analysis often requires visual inspection of frequency content, tempo, and structure, but setting up spectrogram tooling in Python or DAWs is slow. This Skill wraps the songsee CLI to produce spectrograms and multi-panel audio feature images directly from audio files. ## Core Features & Use Cases - Spectrogram Generation: Render standard, mel-scaled, and styled spectrograms from WAV or MP3 files with a single command. - Multi-Panel Feature Grids: Combine chroma, MFCC, tempogram, loudness, HPSS, self-similarity, and spectral flux visualizations into one image. - Time Slicing and Format Control: Extract specific audio segments with --start/--duration and output PNG or JPG at custom dimensions. - Use Case: Compare two synthesized audio outputs by generating mel spectrograms of each, then inspect the images with vision_analyze to detect artifacts or differences. ## Quick Start Use the songsee skill to generate a mel spectrogram of track.mp3 and save it as spectrogram.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 MP3 file?▼

Run songsee track.mp3 to produce a default spectrogram, or add -o spectrogram.png to choose the output file. Use --viz mel for a mel-scaled spectrogram and --style to pick a color palette like magma or viridis.

How to visualize multiple audio features in one image?▼

Pass comma-separated types to --viz, for example --viz spectrogram,mel,chroma,mfcc,tempogram. songsee renders all selected visualizations as a grid in a single output image.

What audio formats does songsee support?▼

songsee decodes WAV and MP3 natively without extra tools. Other formats such as FLAC or AAC require ffmpeg to be installed for decoding.

Can I generate a spectrogram of only part of an audio file?▼

Yes, use --start and --duration to slice the audio, for example --start 12.5 --duration 8 renders an 8-second segment starting at 12.5 seconds. You can also pipe audio via stdin.

Why does songsee fail to process my audio file?▼

Failures usually occur when the songsee binary is not installed via go install, or when the input format is not WAV/MP3 and ffmpeg is missing. Verify both prerequisites and check the file path or stdin input.

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