voice-ai-development

Role: Voice AI Architect

davila7/claude-code-templates|Updated Apr 8, 2026

Works with

Claude CodeCursorClineWindsurfCodexGoose

Installation Guide

Select your AI agent

How to use voice-ai-development on Cursor

AI-first code editor with Composer

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

›Cursor installed and configured on your machine
›Node.js 16+ with npm — verify with node --version
›Active project directory where you want to add voice-ai-development

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/davila7/claude-code-templates --skill voice-ai-development

Fetches voice-ai-development from davila7/claude-code-templates and configures it for Cursor.

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?

│

│ ── Universal (.agents/skills) ────────────────

│ · Cline · Codex · Goose · Windsurf

│ ●Cursor(selected)

│ · Cursor · Aider · Continue

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/voice-ai-development

Restart Cursor to activate voice-ai-development. Access via /voice-ai-development in your agent's command palette.

⚠

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

›View source on GitHub ›Skills CLI docs ›About Cursor ›What are agent skills?

Documentation

List & Monetize Your Skill

Submit your Claude Code skill and start earning

Get started →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

✓

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

✓

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

✓

Improve work quality by 30-40% with less effort

Voice AI Development

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.

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", "audio": base64.b64encode(audio_bytes).decode() })) # Receive events async for message in ws: event = json.loads(message) if event["type"] == "resp

Vapi Voice Agent

Build voice agents with Vapi platform

When to use: Phone-based agents, quick deployment

# Vapi provides hosted voice agents with webhooks from flask import Flask, request, jsonify import vapi app = Flask(__name__) client = vapi.Vapi(api_key="...") # Create an assistant assistant = client.assistants.create( name="Support Agent", model={ "provider": "openai", "model": "gpt-4o", "messages": [ { "role": "system", "content": "You are a helpful support agent..." } ] }, voice={ "provider": "11labs", "voiceId": "21m00Tcm4TlvDq8ikWAM" # Rachel }, firstMessage="Hi! How can I help you today?", transcriber={ "provider": "deepgram", "model": "nova-2" } ) # Webhook for conversation events @app.route("/vapi/webhook", methods=["POST"]) def vapi_webhook(): event = request.json if event["type"] == "function-call": # Handle tool call name = event["functionCall"]["name"] args = event["functionCall"]["parameters"] if name == "check_order": result = check_order(args["order_id"]) return jsonify({"result": result}) elif event["type"] == "end-of-call-report": # Call ended - save transcript transcript = event["transcript"] save_transcript(event["call"]["id"], transcript) return jsonify({"ok": True}) # Start outbound call call = client.calls.create( assistant_id=assistant.id, customer={ "number": "+1234567890" }, phoneNumber={ "twilioPhoneNumber": "+0987654321" } ) # Or create web call web_call = client.calls.create( assistant_id=assistant.id, type="web" ) # Returns URL for WebRTC connection

Deepgram STT + ElevenLabs TTS

Best-in-class transcription and synthesis

When to use: High quality voice, custom pipeline

import asyncio from deepgram import DeepgramClient, LiveTranscriptionEvents from elevenlabs import ElevenLabs # Deepg

voice-ai-development

Installation Guide

How to use voice-ai-development on Cursor

Prerequisites

Run the install command

Select Cursor when prompted

Verify installation

Security Notice

Documentation

List & Monetize Your Skill

Use Cases

Task Automation & Efficiency

Knowledge Enhancement

Quality Improvement

Install Skill

Voice AI Development

Capabilities

Requirements

Patterns

OpenAI Realtime API

Vapi Voice Agent

Deepgram STT + ElevenLabs TTS

`Implementation Guide`

`Best Practices`

`When to Use This`

`Learning Path`

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