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 open-vela/.claude --skill pcm-audiogit clone --depth 1 https://github.com/open-vela/.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/open-vela/.claude/pcm-audio)<a href="https://agentmods.dev/skills/open-vela/.claude/pcm-audio"><img src="https://agentmods.dev/badge/skills/open-vela/.claude/pcm-audio/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/open-vela/.claude/pcm-audio"><img src="https://agentmods.dev/badge/skills/open-vela/.claude/pcm-audio.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00048 | $0.02463 |
| Opus 5 | $0.00024 | $0.01231 |
| Sonnet 5 | $0.00010 | $0.00493 |
| Haiku 4.5 | $0.00005 | $0.00246 |
Grade A, and why
pcm-audio 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 11d 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 — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PCM Audio Quality Analysis Skill
概述
分析PCM音频文件的质量问题，包括削波失真、静音插入、爆破音、底噪、周期性失真等，并将问题特征与可能的代码错误对应起来。
适用场景
- 音频采集/播放出现杂音、噪音、爆音
- 音频流中出现静音段、断断续续
- 音频质量下降、失真
- 需要定位音频处理代码的bug
支持的音频格式
- PCM格式: RAW PCM、.pcm文件
- 采样率: 8kHz - 48kHz
- 位宽: 16-bit (int16)
- 声道: 单声道/立体声/多声道
🚀 使用方法
命令行调用
```bash
分析单声道16kHz PCM文件
python scripts/audio_analyzer.py input.pcm --sample-rate 16000 --channels 1
分析立体声48kHz文件
python scripts/audio_analyzer.py stereo.pcm --sample-rate 48000 --channels 2
不生成图表（加快速度）
python scripts/audio_analyzer.py input.pcm --no-visualize ```
Python API调用
```python import sys sys.path.append('scripts') from audio_analyzer import AudioQualityAnalyzer
创建分析器（注意：根据实际文件调整参数）
analyzer = AudioQualityAnalyzer( pcm_file='input.pcm', sample_rate=16000, channels=1 # 1=单声道, 2=立体声 )
完整分析
results = analyzer.analyze_all()
单项检测
clipping = analyzer.detect_clipping() silence = analyzer.detect_silence_insertion() clicks = analyzer.detect_clicks()
自定义阈值
analyzer.detect_clipping(threshold=0.95) # 更严格 analyzer.detect_clicks(threshold=3000) # 更敏感
生成可视化
analyzer.visualize('output.png') ```
参数说明
| 参数 | 说明 | 默认值 | 示例 |
|---|---|---|---|
pcm_file |
PCM文件路径 | 必填 | input.pcm |
--sample-rate |
采样率(Hz) | 16000 | 48000 |
--channels |
声道数 | 2 | 1, 8 |
--sample-width |
样本宽度(字节) | 2 | 2 |
--output |
输出图表文件 | audio_analysis.png |
result.png |
--no-visualize |
不生成图表 | False | - |
🔍 核心检测能力
1. 削波失真检测
调用: `analyzer.detect_clipping(threshold=0.98)`
返回值: `{'clipped_pct': float, 'clipped_samples': int, 'max_consecutive': int, 'is_severe': bool}`
问题映射:
- 削波率 > 1% → 音量增益过大、整数溢出、格式转换错误
2. 静音插入检测
调用: `analyzer.detect_silence_insertion(window_size=1600)`
返回值: `[{'start_time_s': float, 'end_time_s': float, 'duration_ms': float, 'zero_pct': float}]`
问题映射:
- 零值 > 50% → Buffer大小错误、未初始化、采样率转换错误
3. 爆破音检测
调用: `analyzer.detect_clicks(threshold=5000)`
What ships with it
3 files 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.
- 11d ago First seen · 277 lines · 48 tokens per session scan A 6af2ccc3a43e
pcm-audio is a skill published in the GitHub repository open-vela/.claude (5 stars, last pushed yesterday), licensed Apache-2.0. It adds 48 tokens to every session and 2,463 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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