bug-reproduce
Turn a known bug into a tight, red-capable reproducer, then prove the reproducer locks that…
Audio spectrograms/features (mel, chroma, MFCC) via CLI.
$ npx -y skills add Prismer-AI/PrismerCloud --skill prismer-songsee --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/prismer-songseeContext preview
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Audio spectrograms/features (mel, chroma, MFCC) via CLI.
name: prismer-songsee
scope: common
category: media
description: "Audio spectrograms/features (mel, chroma, MFCC) via CLI."
version: 1.0.0
author: community
license: MIT
platforms: [ linux, macos, windows ]
metadata:
nativeReplaces: [ songsee ]
hermes:
tags: [ Audio, Visualization, Spectrogram, Music, Analysis ]
homepage: https://github.com/steipete/songsee
requiresExplicitGrant: true
prerequisites:
commands: [ songsee ]Generate spectrograms and multi-panel audio feature visualizations from audio files.
Requires [Go](https://go.dev/doc/install):
go install "github.com/steipete/songsee/cmd/songsee@${SONGSEE_VERSION:?Set an exact reviewed release or commit}"Optional: `ffmpeg` for formats beyond WAV/MP3.
# 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
Use `--viz` with comma-separated values:
| Type | Description | |------|-------------| | `spectrogram` | Standard frequency spectrogram | | `mel` | Mel-scaled spectrogram | | `chroma` | Pitch class distribution | | `hpss` | Harmonic/percussive separation | | `selfsim` | Self-similarity matrix | | `loudness` | Loudness over time | | `tempogram` | Tempo estimation | | `mfcc` | Mel-frequency cepstral coefficients | | `flux` | Spectral flux (onset detection) |
Multiple `--viz` types render as a grid in a single image.
| Flag | Description | |------|-------------| | `--viz` | Visualization types (comma-separated) | | `--style` | Color palette: `classic`, `magma`, `inferno`, `viridis`, `gray` | | `--width` / `--height` | Output image dimensions | | `--window` / `--hop` | FFT window and hop size | | `--min-freq` / `--max-freq` | Frequency range filter | | `--start` / `--duration` | Time slice of the audio | | `--format` | Output format: `jpg` or `png` | | `-o` | Output file path |
Record `songsee --help` and the installed version/build provenance. Use a task-owned output path; never overwrite input audio. Probe input duration/channels before decoding, cap file size and rendering time to the task budget, and test the actual requested codec. Core analysis is local and needs no account. A passing WAV smoke does not establish support for every codec or OS.
Repo: Prismer-AI/PrismerCloud
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