Agent skill · AI & Agents

voice-ai

Production voice AI agents with sub-500ms latency. Groq LLM, Deepgram STT, Cartesia TTS, Twilio integration. No OpenAI. Use when: voice agent, phone bot, STT, TTS, Deepgram, Cartesia, Twilio, voice AI, speech to text, IVR, call center, voice latency.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill voice-ai-skill --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 14 KB
Bundled scripts: none
Path: skills/ai-llm/voice-ai-skill/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

<objective> Build production voice AI agents with sub-500ms latency: 1. **STT** - Deepgram Nova-3 streaming transcription (~150ms) 2. **LLM** - Groq llama-3.1-8b-instant for fastest inference (~220ms) 3. **TTS** - Cartesia Sonic for ultra-realistic voice (~90ms) 4. **Telephony** - Twilio Media Streams for real-time bidirectional audio **CRITICAL: NO OPENAI - Never use `from openai import OpenAI`** Key deliverables: - Streaming STT with voice activity detection - Low-latency LLM responses optimized for voice - Expressive TTS with emotion controls - Twilio Media Streams WebSocket handler </objective> <quick_start> **Minimal Voice Pipeline (~50 lines, <500ms):** ```python import os import asyncio from groq import AsyncGroq from deepgram import AsyncDeepgramClient from cartesia import AsyncCartesia # NEVER: from openai import OpenAI async def voice_pipeline(user_audio: bytes) -> bytes: """Process audio input, return audio response.""" # 1. STT: Deepgram Nova-3 (~150ms) dg = AsyncDeepgramClient(api_key=os.getenv("DEEPGRAM_API_KEY")) result = await dg.listen.rest.v1.transcribe( {"buffer": user_audio, "mimetype": "audio/wav"}, {"model": "nova-3", "language": "en-US"} ) user_text = result.

What's inside
Steps it walks through
  1. VozLux-Tested Stack
  2. LLM Priority (Never OpenAI)
  3. Tier Architecture
  4. Deepgram STT (v5 SDK)
  5. Streaming WebSocket Pattern
  6. Connection Options
  7. Groq LLM (Fastest Inference)
  8. Voice-Optimized Pattern
  9. Model Selection
  10. Cartesia TTS (Sonic-2)
  11. Streaming Pattern
  12. With Timestamps
  13. Twilio Media Streams
  14. WebSocket Handler (FastAPI)
Ships with 1 file
  • metadata.json
Commands it runs
Required (NEVER OpenAI)
Twilio
Fallbacks
pip install deepgram-sdk groq cartesia twilio fastapi
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About this skill
What does the voice-ai skill do?

Production voice AI agents with sub-500ms latency. Groq LLM, Deepgram STT, Cartesia TTS, Twilio integration. No OpenAI. Use when: voice agent, phone bot, STT, TTS, Deepgram, Cartesia, Twilio, voice AI, speech to text, IVR, call center, voice latency.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill voice-ai-skill --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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