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 autonomous-ai/autonomous-os --skill audiogit clone --depth 1 https://github.com/autonomous-ai/autonomous-osWrote 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/autonomous-ai/autonomous-os/audio)<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/audio"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/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/autonomous-ai/autonomous-os/audio"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/audio.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 44 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00036 | $0.01086 |
| Opus 5.5 | $0.00014 | $0.00434 |
| Sonnet 5.5 | $0.00007 | $0.00217 |
| Haiku 4.5 | $0.00004 | $0.00109 |
Grade A, and why
audio scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Use `Bash` with `curl` to call the HTTP API at `http://127.0.0.1:5001`. How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audio Control
Quick Start
Control the device's speaker and microphone hardware directly. Use this for volume adjustments, test tones, and raw audio recording. This is LOW-LEVEL hardware control only.
Workflow
- Determine the user's audio hardware need:
- Volume adjustment -> use
POST /audio/volume - Check current volume -> use
GET /audio/volume - Diagnostics / test -> use
POST /audio/play-tone - Raw recording -> use
POST /audio/record
- Volume adjustment -> use
- For explicit volume/tone/recording requests, call the requested endpoint directly and handle its response. Use
GET /audiofor device diagnostics, not routine preflight. Relative volume changes still needGET /audio/volume. - Execute the appropriate API call
- Confirm the action to the user
Examples
Input: "Louder please" / "Turn it up"
Output: Check current volume with GET /audio/volume, then increase by ~15 with POST /audio/volume. Confirm: "Volume set to 85%."
Input: "Set volume to 50%"
Output: Call POST /audio/volume with {"volume": 50}. Confirm: "Volume set to 50%."
Input: "Mute" / "Too loud"
Output: Call POST /audio/volume with {"volume": 0}. Confirm: "Muted."
Input: "I can't hear you"
Output: Check current volume with GET /audio/volume, then increase it. Confirm with the new level.
Input: "Say something" / "Tell me a joke" Output: Do NOT use this skill. Just reply normally — your voice pipeline handles TTS automatically.
Tools
Use Bash with curl to call the HTTP API at http://127.0.0.1:5001.
Check audio devices
curl -s http://127.0.0.1:5001/audio
Response:
{
"output_device": 0,
"input_device": 1,
"available": true
}
Set volume
curl -s -X POST http://127.0.0.1:5001/audio/volume \
-H "Content-Type: application/json" \
-d '{"volume": 70}'
Volume range: 0 (mute) to 100 (max).
Get current volume
curl -s http://127.0.0.1:5001/audio/volume
Response: {"control": "Speaker", "volume": 70}
Play test tone
curl -s -X POST "http://127.0.0.1:5001/audio/play-tone?frequency=440&duration_ms=500"
Plays a sine wave. Use for audio testing only. Keep it short (< 1 second).
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.
- 1mo ago Changed · +4 lines 815d7e7d9642
- 1mo ago First seen · 102 lines · 36 tokens per session scan A c36fc4990968
audio is a skill published in the GitHub repository autonomous-ai/autonomous-os (378 stars, last pushed 18d ago), licensed Apache-2.0. It adds 36 tokens to every session and 1,086 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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