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 skills/godot-fun/godot-framework/audio-denoisenpx skills add godot-fun/godot-framework --skill audio-denoisegit clone --depth 1 https://github.com/godot-fun/godot-frameworkWrote 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/godot-fun/godot-framework/audio-denoise)<a href="https://agentmods.dev/skills/godot-fun/godot-framework/audio-denoise"><img src="https://agentmods.dev/badge/skills/godot-fun/godot-framework/audio-denoise.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 | $0.00048 | $0.00500 |
| Opus 5 | $0.00024 | $0.00250 |
| Sonnet 5 | $0.00010 | $0.00100 |
| Haiku 4.5 | $0.00005 | $0.00050 |
Grade A, and why
audio-denoise 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 5d 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.
What it actually says
Audio Denoise
Reduce background noise via FFmpeg afftdn.
Rules
When this skill applies, read and follow skill-dependency-manager �?run scripts as documented, install missing tools into .dependency/.
Quick Start
Denoise a single audio file, output to <audio-dir>/audio-denoise/<audio-name>:
.dependency/python/python .ai/audio-denoise/denoise.py --audio path/to/audio.wav
Defaults
| Setting | Default | Notes |
|---|---|---|
| Denoise | afftdn |
nr=10 dB, nf=-25 dB �?conservative for SFX |
Common Flags
--audio · --nr · --nf · --output
.dependency/python/python .ai/audio-denoise/denoise.py --audio Audio/SFX/click.wav
.dependency/python/python .ai/audio-denoise/denoise.py --audio Audio/Voice/line.wav --nr 8
Originals are never modified. Input must be a single audio file (--audio), not a directory. Supported: .wav, .mp3, .ogg, .flac, .aac, .m4a, .wma.
Agent Notes
- Use the bundled script, not hand-written
afftdnfilters. - Default is light denoise �?do not raise
--nrunless the user asks; heavy denoise dulls transients. - Missing Python/FFmpeg �?populate
.dependency/per skill-dependency-manager, retry same command. - Do not copy, move, or replace the source with denoised output �?tell the user where
audio-denoise/files are; they swap assets manually when ready.
Tests
From repo root:
.dependency/python/python .ai/audio-denoise/test_denoise.py
Manual CLI examples: cli/audio-denoise.md
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.
- 5d ago First seen · 55 lines · 48 tokens per session scan A 693543a727aa
audio-denoise is a skill published in the GitHub repository godot-fun/godot-framework (116 stars, last pushed 5d ago), licensed MIT. It adds 48 tokens to every session and 500 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 2026-08-30.
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