Voice Ai Development
Architect low-latency voice agents and voice-enabled apps using Realtime API, Vapi, Deepgram, ElevenLabs, LiveKit, and WebRTC.
Overview
Voice AI Development is an agent skill most often used in Build (also Ship) that designs production voice agents with Realtime API, Vapi, Deepgram, ElevenLabs, LiveKit, and WebRTC.
Install
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill voice-ai-developmentWhat is this skill?
- Covers OpenAI Realtime API, Vapi agents, Deepgram STT/TTS, and ElevenLabs synthesis
- Includes LiveKit real-time infrastructure and WebRTC audio handling guidance
- Frames design around latency budgets, audio quality, and perceived responsiveness
- Supports voice agent architecture and provider selection for production readiness
- Lists async programming as a foundational prerequisite for streaming pipelines
Adoption & trust: 690 installs on skills.sh; 40.1k GitHub stars; 2/3 security scanners passed (skills.sh audits).
What problem does it solve?
You are stitching voice STT, TTS, and realtime transport together but lack a cohesive architecture that keeps latency and audio quality under control.
Who is it for?
Builders creating real-time voice agents or voice-enriched web apps who must pick and combine commercial audio AI APIs.
Skip if: Text-only chatbots, offline batch transcription scripts with no realtime constraint, or projects with zero network audio requirements.
When should I use this skill?
Building real-time voice agents or voice-enabled applications requiring provider selection, streaming, and latency optimization.
What do I get? / Deliverables
You get provider-aware voice agent guidance with streaming, latency optimization, and WebRTC-oriented implementation choices for shippable voice UX.
- Voice agent architecture sketch
- Provider stack recommendation
- Latency and audio quality tuning checklist
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Voice stacks are integrated during Build when wiring providers and real-time audio paths, with Ship perf tuning as a common follow-on. Integrations captures multi-vendor STT, TTS, realtime, and WebRTC plumbing rather than static frontend styling alone.
Where it fits
Choose Deepgram vs bundled Realtime STT and wire ElevenLabs TTS into a Vapi or custom agent loop.
Design tool-calling voice agent flows with async streaming handlers.
Profile end-to-end mouth-to-ear latency and tune buffers before public beta.
How it compares
Use for full voice pipeline architecture instead of a single-vendor STT snippet with no WebRTC or agent orchestration context.
Common Questions / FAQ
Who is voice-ai-development for?
Solo and indie developers building voice agents or voice-enabled products who need multi-provider realtime audio expertise in the agent.
When should I use voice-ai-development?
During Build integrations when wiring Realtime API or Vapi, and during Ship perf when tuning latency and audio quality before users talk to your app.
Is voice-ai-development safe to install?
It implies network and API usage for third-party voice services; review the Security Audits panel on this Prism page and your API key handling policies.
SKILL.md
READMESKILL.md - Voice Ai Development
# Voice AI Development Expert in building voice AI applications - from real-time voice agents to voice-enabled apps. Covers OpenAI Realtime API, Vapi for voice agents, Deepgram for transcription, ElevenLabs for synthesis, LiveKit for real-time infrastructure, and WebRTC fundamentals. Knows how to build low-latency, production-ready voice experiences. **Role**: Voice AI Architect You are an expert in building real-time voice applications. You think in terms of latency budgets, audio quality, and user experience. You know that voice apps feel magical when fast and broken when slow. You choose the right combination of providers for each use case and optimize relentlessly for perceived responsiveness. ### Expertise - Real-time audio streaming - Voice agent architecture - Provider selection - Latency optimization - Audio quality tuning ## Capabilities - OpenAI Realtime API - Vapi voice agents - Deepgram STT/TTS - ElevenLabs voice synthesis - LiveKit real-time infrastructure - WebRTC audio handling - Voice agent design - Latency optimization ## Prerequisites - 0: Async programming - 1: WebSocket basics - 2: Audio concepts (sample rate, codec) - Required skills: Python or Node.js, API keys for providers, Audio handling knowledge ## Scope - 0: Latency varies by provider - 1: Cost per minute adds up - 2: Quality depends on network - 3: Complex debugging ## Ecosystem ### Primary - OpenAI Realtime API - Vapi - Deepgram - ElevenLabs ### Infrastructure - LiveKit - Daily.co - Twilio ### Common_integrations - WebRTC - WebSockets - Telephony (SIP/PSTN) ### Platforms - Web applications - Mobile apps - Call centers - Voice assistants ## Patterns ### OpenAI Realtime API Native voice-to-voice with GPT-4o **When to use**: When you want integrated voice AI without separate STT/TTS import asyncio import websockets import json import base64 OPENAI_API_KEY = "sk-..." async def voice_session(): url = "wss://api.openai.com/v1/realtime?model=gpt-4o-realtime-preview" headers = { "Authorization": f"Bearer {OPENAI_API_KEY}", "OpenAI-Beta": "realtime=v1" } async with websockets.connect(url, extra_headers=headers) as ws: # Configure session await ws.send(json.dumps({ "type": "session.update", "session": { "modalities": ["text", "audio"], "voice": "alloy", # alloy, echo, fable, onyx, nova, shimmer "input_audio_format": "pcm16", "output_audio_format": "pcm16", "input_audio_transcription": { "model": "whisper-1" }, "turn_detection": { "type": "server_vad", # Voice activity detection "threshold": 0.5, "prefix_padding_ms": 300, "silence_duration_ms": 500 }, "tools": [ { "type": "function", "name": "get_weather", "description": "Get weather for a location", "parameters": { "type": "object", "properties": { "location": {"type": "string"} } } } ] } })) # Send audio (PCM16, 24kHz, mono) async def send_audio(audio_bytes): await ws.send(json.dumps({ "type": "input_audio_buffer.append",