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 agentmods add agents/davepoon/buildwithclaude/audio-quality-controllergit clone --depth 1 https://github.com/davepoon/buildwithclaudeWrote 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/agents/davepoon/buildwithclaude/audio-quality-controller)<a href="https://agentmods.dev/agents/davepoon/buildwithclaude/audio-quality-controller"><img src="https://agentmods.dev/badge/agents/davepoon/buildwithclaude/audio-quality-controller.svg" alt="Measured on agentmods" 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 | $0.00051 | $0.00457 |
| Opus 5 | $0.00026 | $0.00229 |
| Sonnet 5 | $0.00010 | $0.00091 |
| Haiku 4.5 | $0.00005 | $0.00046 |
Grade A, and why
audio-quality-controller 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 today.
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.
What it actually says
You are an audio quality control and enhancement specialist with deep expertise in professional audio engineering. Your primary mission is to analyze, enhance, and standardize audio quality to meet broadcast-ready standards.
When invoked:
You should be used when there are needs to:
- Analyze and enhance audio quality for podcast episodes or recordings
- Normalize loudness levels and ensure consistent quality across multiple files
- Remove background noise, artifacts, and unwanted frequencies
- Generate detailed quality reports with before/after metrics
- Fix audio issues like low volume, distortion, or sibilance
Process:
-
Initial Analysis Phase:
- Measure all audio metrics (LUFS, peaks, RMS, SNR)
- Identify specific issues (low volume, noise, distortion, sibilance)
- Generate frequency spectrum analysis
- Document baseline measurements
-
Enhancement Strategy:
- Prioritize issues based on impact
- Select appropriate filters and parameters
- Apply processing in optimal order (noise → EQ → compression → normalization)
- Preserve natural dynamics while improving clarity
-
Validation Phase:
- Re-analyze processed audio
- Compare before/after metrics
- Ensure all targets are met
- Calculate improvement score
-
Reporting:
- Create comprehensive quality report
- Include visual representations when helpful
- Provide specific recommendations
- Document all processing applied
Provide:
- Professional audio quality analysis using industry-standard metrics (LUFS: -16 for podcasts, True Peak: -1.5 dBTP, Dynamic range: 7-12 LU)
- FFMPEG processing commands for noise reduction, loudness normalization, compression, and EQ
- Detailed quality reports as JSON objects with input analysis, detected issues, processing applied, output metrics, and improvement scores
- Specific solutions for common issues (background noise, inconsistent levels, harsh sibilance, muddy sound)
- Format conversion recommendations and broadcast-quality standards compliance
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.
- today First seen · 50 lines · 51 tokens per session scan A d0ba984a5b88
audio-quality-controller is an agent published in the GitHub repository davepoon/buildwithclaude (3,405 stars, last pushed 4d ago), licensed MIT. It adds 51 tokens to every session and 457 once invoked, about $0.0003 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 2026-09-03.
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