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 mcp-tool-shop-org/mcp-voice-soundboard --skill statusgit clone --depth 1 https://github.com/mcp-tool-shop-org/mcp-voice-soundboardWrote 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/mcp-tool-shop-org/mcp-voice-soundboard/status)<a href="https://agentmods.dev/skills/mcp-tool-shop-org/mcp-voice-soundboard/status"><img src="https://agentmods.dev/badge/skills/mcp-tool-shop-org/mcp-voice-soundboard/status/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/mcp-tool-shop-org/mcp-voice-soundboard/status"><img src="https://agentmods.dev/badge/skills/mcp-tool-shop-org/mcp-voice-soundboard/status.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 | $0.00009 | $0.00257 |
| Opus 5 | $0.00005 | $0.00129 |
| Sonnet 5 | $0.00002 | $0.00051 |
| Haiku 4.5 | $0.00001 | $0.00026 |
Grade A, and why
status 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.
What it actually says
Voice Status
Check the voice engine health and report status.
Instructions
-
Call
voice_statusto get engine health information -
Report:
- Engine status — healthy / degraded / unhealthy
- Backend — which TTS backend is active (mock, http, python)
- Voice count — how many voices are available
- Preset count — how many presets are configured
- Ambient system — enabled or disabled
- Guardrails — rate limits, concurrency, timeout settings
- Any errors or warnings
-
If the engine is unhealthy, suggest:
- Check that the TTS backend is running
- Verify environment variables are set correctly
- Check
VOICE_SOUNDBOARD_BACKENDsetting - For HTTP backend: verify
VOICE_SOUNDBOARD_HTTP_URLis reachable
Tips
- The mock backend always works — it returns silence but validates the full pipeline
- For real audio, configure the HTTP or Python backend
voice_statusis lightweight and not rate-limited — safe to call frequently
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 · 35 lines · 9 tokens per session scan A 09f3cbb10687
status is a skill published in the GitHub repository mcp-tool-shop-org/mcp-voice-soundboard (0 stars, last pushed 5d ago), licensed MIT. It adds 9 tokens to every session and 257 once invoked, about $0.0000 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.
Other skills, from other repositories
sag
ElevenLabs text-to-speech with mac-style say UX.
ElevenLabs — Living Voice
Use when writing or tuning ElevenLabs speech so it sounds alive, paced, and human; covers text shaping for Eleven Multilingual v2 and Eleven v3, plus API-based voice-setting updates from user feedback.
c-voice
Convert speech to text using sag (ElevenLabs STT) and synthesize speech using say (macOS built-in TTS). Enables voice input transcription and audio output.
character-matrix
How to interpret the noisy-coding Character Matrix — the four personality sliders (humor, honesty, brevity, chatty) set on the dashboard and delivered as [CHARACTER] instructions. Use whenever a [CHARACTER] instruction arrives, when speaking through the noisy-coding speak tool, or when the user asks about tuning your…
voice-conversations
How voice conversations work with the noisy-coding plugin — trusting [VOICE] messages, answering aloud with the speak tool, spoken-reply conventions, and troubleshooting. Use whenever a message tagged [VOICE] arrives, when the mcpnoisy-codingspeak tool is available, or when the user asks about the voice system.
voice-ai
Use when voice AI — text-to-speech (ElevenLabs, OpenAI TTS), speech-to-text (Whisper), voice cloning, real-time voice agents. Use when working with voice ai.