audio-analysis
audio-analysis provides tools to decompose audio signals into their frequency components using FFT algorithms, enabling detailed spectral visualization and analysis. Extract magnitude and phase data across the frequency spectrum to understand audio characteristics, detect patterns, and power advanced audio processing workflows.
audio-analysis provides FFT-based tools to decompose audio signals into frequency components. Use the library's frequency extraction methods to obtain magnitude and phase data across the spectrum, enabling you to visualize spectral content and analyze audio characteristics for reactive effects and advanced processing workflows.
AI-generated summary based on this skill's SKILL.md
Decision gist · record as of 2026-07-27
audio-analysis provides FFT-based tools to decompose audio signals into frequency components. Use the library's frequency extraction methods to obtain magnitude and phase data across the spectrum, enabling you to visualize spectral content and analyze audio characteristics for reactive effects and advanced processing workflows.
Use it when
- Yes, audio-analysis includes beat detection capabilities that identify audio energy peaks in real-time.
- audio-analysis measures amplitude, RMS (root mean square), and volume levels in real-time.
Verify before relying
Read SKILL.md below before installing (2 files). Open directory: indexed for reading, not audited.
Install
Bbeierle12/Skill-MCP-Claude/audio-analysis · repository language: JavaScript
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Frequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
How do I extract frequency data from audio with audio-analysis?
audio-analysis provides FFT-based tools to decompose audio signals into frequency components. Use the library's frequency extraction methods to obtain magnitude and phase data across the spectrum, enabling you to visualize spectral content and analyze audio characteristics for reactive effects and advanced processing workflows.
Can audio-analysis detect beats and audio energy peaks?
Yes, audio-analysis includes beat detection capabilities that identify audio energy peaks in real-time. By analyzing frequency bands and energy levels, the library helps you detect beat patterns and sync reactive visualizations to musical timing, making it ideal for audio-reactive applications.
What audio measurements does audio-analysis provide in real-time?
audio-analysis measures amplitude, RMS (root mean square), and volume levels in real-time. These measurements let you monitor audio intensity across time, supporting dynamic visualization updates and responsive audio processing based on current signal strength.
How does audio-analysis handle waveform and frequency band analysis?
audio-analysis analyzes both waveform data and individual frequency bands to characterize audio content. By examining specific frequency ranges, you can detect bass, midrange, and treble components separately, enabling granular control over audio-reactive features and targeted frequency-based effects.
Does audio-analysis smooth and normalize audio data for visualization?
audio-analysis includes smoothing and normalization tools to stabilize audio data for consistent visualizations. These features reduce noise and fluctuations, ensuring smooth animations and reliable reactive effects even with variable input levels or noisy audio sources.
What license does audio-analysis use?
audio-analysis is released under the MIT license, allowing free use, modification, and distribution in both open-source and commercial projects with minimal restrictions.
SKILL.md
Rendered from the published skill. Quoted content, verbatim.
Audio Analysis
FFT, frequency extraction, and audio data analysis.
Quick Start
import * as Tone from 'tone';
// Create analyzer
const analyser = new Tone.Analyser('fft', 256);
const player = new Tone.Player('/audio/music.mp3');
player.connect(analyser);
player.toDestination();
// Get frequency data
const frequencyData = analyser.getValue(); // Float32Array
Analyzer Types
FFT Analyzer
// FFT (Fast Fourier Transform) - frequency spectrum
const fftAnalyser = new Tone.Analyser({
type: 'fft',
size: 256, // Must be power of 2: 32, 64, 128, 256, 512, 1024, 2048
smoothing: 0.8 // 0-1, higher = smoother transitions
});
// Returns Float32Array of dB values (typically -100 to 0)
const fftData = fftAnalyser.getValue();
Waveform Analyzer
```javascript // Waveform - time domain data const waveformAnalyser = new Tone.Analyser({ type:
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skills/audio-analysis/SKILL.md
skills/audio-analysis/_meta.json
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