Generate audio spectrograms and multi-feature visualizations from audio files.
npx skills add https://github.com/ruiyangruiyi/hermes-agent --skill songsee-ruiyangruiyi
Please help me install this Agent Skill. Skill: songsee Source: https://github.com/ruiyangruiyi/hermes-agent/tree/main/skills/media/songsee Command: npx skills add https://github.com/ruiyangruiyi/hermes-agent --skill songsee-ruiyangruiyi
Turning raw audio into useful visual representations and audio features is slow and repetitive when you have to manually configure transforms and plots, especially when you need consistent outputs for analysis, documentation, or debugging.
Run the command songsee track.mp3 --viz spectrogram,mel,chroma,mfcc,loudness --format png -o features.png to create a multi-panel visualization from your audio file.
High-intent search queries and answers about installing and using this skill.
To generate an audio spectrogram from an MP3, run the songsee CLI with your track and specify visualization types like spectrogram or mel, then output the results as a PNG image for visual inspection of timbre and energy distribution.
Visualizing MFCC and chroma features for music analysis is done by running a CLI command that produces multi-panel images, allowing you to inspect multiple audio characteristics simultaneously for deeper sound understanding.
Yes, you can analyze specific time windows of an audio track by using time-sliced rendering options, which creates visuals for targeted segments and fits iterative workflows in audio research and production debugging.
For audio debugging and documentation, you can extract multi-feature visualizations including chroma, MFCC, loudness, tempogram, spectral flux, and self-similarity, exporting them as multi-panel images to interpret sound content over time.
Rendering mel-scaled spectrograms requires the songsee CLI to compute representations, but the Skill itself operates without external dependencies, allowing you to directly generate and export images with selectable visualization types and formats.
While batch-friendly CLI workflows are supported for full tracks or time windows, limitations depend on your local environment's ability to run the CLI for computing spectrogram-like representations and exporting multi-panel images consistently.
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