Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Bbeierle12/Skill-MCP-Claude --skill audio-analysisgit clone --depth 1 https://github.com/Bbeierle12/Skill-MCP-ClaudeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/bbeierle12/skill-mcp-claude/audio-analysis)<a href="https://agentmods.dev/skills/bbeierle12/skill-mcp-claude/audio-analysis"><img src="https://agentmods.dev/badge/skills/bbeierle12/skill-mcp-claude/audio-analysis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/bbeierle12/skill-mcp-claude/audio-analysis"><img src="https://agentmods.dev/badge/skills/bbeierle12/skill-mcp-claude/audio-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.02945 |
| Opus 5 | $0.00023 | $0.01473 |
| Sonnet 5 | $0.00009 | $0.00589 |
| Haiku 4.5 | $0.00005 | $0.00295 |
Grade A, and why
audio-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 466 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
// Waveform - time domain data
const waveformAnalyser = new Tone.Analyser({
type: 'waveform',
size: 1024
});
// Returns Float32Array of amplitude values (-1 to 1)
const waveformData = waveformAnalyser.getValue();
Meter (Volume Level)
// Meter - overall volume level
const meter = new Tone.Meter({
smoothing: 0.9,
normalRange: false // true for 0-1, false for dB
});
player.connect(meter);
// Get current level
const level = meter.getValue(); // dB or 0-1
FFT Size Impact
| Size | Frequency Resolution | Time Resolution | Use Case |
|---|---|---|---|
| 32 | Low | High | Beat detection |
| 128 | Medium | Medium | General visualization |
| 256 | Good | Good | Balanced (default) |
| 1024 | High | Low | Detailed spectrum |
| 2048 | Very High | Very Low | Audio analysis tools |
Frequency Bands
Manual Band Extraction
const analyser = new Tone.Analyser('fft', 256);
function getFrequencyBands() {
const data = analyser.getValue();
const binCount = data.length;
// Define frequency band ranges (approximate for 44.1kHz sample rate)
// Each bin = (sampleRate / 2) / binCount Hz
const bands = {
sub: average(data, 0, Math.floor(binCount * 0.03)), // ~20-60 Hz
bass: average(data, Math.floor(binCount * 0.03), Math.floor(binCount * 0.08)), // ~60-250 Hz
lowMid: average(data, Math.floor(binCount * 0.08), Math.floor(binCount * 0.15)), // ~250-500 Hz
mid: average(data, Math.floor(binCount * 0.15), Math.floor(binCount * 0.3)), // ~500-2000 Hz
highMid: average(data, Math.floor(binCount * 0.3), Math.floor(binCount * 0.5)), // ~2000-4000 Hz
high: average(data, Math.floor(binCount * 0.5), binCount) // ~4000+ Hz
};
return bands;
}
function average(data, start, end) {
let sum = 0;
for (let i = start; i < end; i++) {
sum += data[i];
}
return sum / (end - start);
}
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 466 lines · 45 tokens per session scan A cd6ba6f3a3b0
audio-analysis is a skill published in the GitHub repository Bbeierle12/Skill-MCP-Claude (8 stars, last pushed yesterday), licensed MIT. It adds 45 tokens to every session and 2,945 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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