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 AkshitIreddy/agent-skills --skill audio-verificationgit clone --depth 1 https://github.com/AkshitIreddy/agent-skillsWrote 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/akshitireddy/agent-skills/audio-verification)<a href="https://agentmods.dev/skills/akshitireddy/agent-skills/audio-verification"><img src="https://agentmods.dev/badge/skills/akshitireddy/agent-skills/audio-verification/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/akshitireddy/agent-skills/audio-verification"><img src="https://agentmods.dev/badge/skills/akshitireddy/agent-skills/audio-verification.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 | $0.00117 | $0.02371 |
| Opus 5 | $0.00059 | $0.01185 |
| Sonnet 5 | $0.00023 | $0.00474 |
| Haiku 4.5 | $0.00012 | $0.00237 |
Grade A, and why
audio-verification 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audio verification
Code that compiles is not sound that works. You cannot hear anything, so an unmeasured audio change is an unverified one. Reading the graph, passing typecheck, and "the node is connected" prove none of: it makes sound at all, it isn't a burst of noise, it doesn't click on attack, it isn't clipping, it isn't inaudibly quiet.
The good news: audio is just numbers. Render the graph offline and every perceptual complaint becomes a measurement.
The rule
Before saying a sound change is done, fixed, or good:
- Render it offline —
OfflineAudioContextgives you the exact samples, deterministically, far faster than real time. - Measure it — peak, spectral flatness, onset, tail (see below).
- A/B against the version you changed — almost every judgement here is relative, not absolute.
- If it doesn't match intent, iterate. If you genuinely can't measure it, say so plainly instead of implying you checked.
Running the probe
scripts/audio-probe.js is a classic script (no imports) so it pastes straight into page.evaluate(), a browser-MCP javascript_tool call, or a devtools console. Evaluating it defines globalThis.AudioProbe.
// build(ctx, destination) wires and starts your nodes — anything you'd build live
const m = await AudioProbe.measure((ctx, dest) => {
const osc = ctx.createOscillator();
const g = ctx.createGain();
g.gain.setValueAtTime(0, 0);
g.gain.linearRampToValueAtTime(0.3, 0.02);
g.gain.exponentialRampToValueAtTime(0.0004, 0.4);
osc.connect(g).connect(dest);
osc.start(0); osc.stop(0.5);
}, { seconds: 0.6 });
// compare variants under identical conditions
const table = await AudioProbe.compare({ before: buildOld, after: buildNew }, { seconds: 0.6 });
Any page will do — about:blank is enough, you don't need the real app to measure a graph. To measure the real code path, either import the module under test, or copy its graph verbatim into build (and say which you did; a hand-copied graph can drift from the source).
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 · 118 lines · 117 tokens per session scan A 42c31797856c
audio-verification is a skill published in the GitHub repository AkshitIreddy/agent-skills (1 stars, last pushed 13d ago), licensed MIT. It adds 117 tokens to every session and 2,371 once invoked, about $0.0006 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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