voice-agent-builder

Build and manage Voice AI agents using Vapi, Bland.ai, or Retell. Create agents, configure voices, set prompts, make outbound calls, and retrieve transcripts. Includes platform comparison guide. Use when building phone agents, IVR systems, or voice-first customer service.

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Install skill "voice-agent-builder" with this command: npx skills add aiwithabidi/voice-agent-pro

Voice Agent Builder

Build, configure, and manage Voice AI agents. Supports Vapi (primary), Bland.ai, and Retell platforms.

Quick Start

export VAPI_API_KEY="your-vapi-api-key"

# Create a voice agent
python3 {baseDir}/scripts/vapi_agent.py create-agent '{"name":"Sales Agent","firstMessage":"Hi! How can I help you today?","systemPrompt":"You are a helpful sales assistant for Acme Corp."}'

# Make an outbound call
python3 {baseDir}/scripts/vapi_agent.py call '{"assistantId":"asst_xxx","phoneNumberId":"pn_xxx","customer":{"number":"+15551234567"}}'

# List agents
python3 {baseDir}/scripts/vapi_agent.py list-agents

# List calls
python3 {baseDir}/scripts/vapi_agent.py list-calls

Platform Comparison

FeatureVapiBland.aiRetell
Best ForCustom agents, dev-friendlySimple outbound campaignsEnterprise, low latency
Latency~800ms~500ms~500ms
Languages100+30+30+
Custom LLM✅ Any OpenAI-compatible✅ Limited✅ Via API
Phone NumbersBuy/importBuy/importBuy/import
Pricing$0.05/min + provider costs$0.09/min all-in$0.07-0.15/min
WebSocket
Knowledge Base✅ Built-in
Transfers

Recommendation: Start with Vapi — most flexible, best docs, largest community. Use Bland for simple high-volume outbound. Use Retell for enterprise low-latency needs.

See {baseDir}/scripts/voice_comparison.md for detailed breakdown.

Agent Creation Workflow

1. Choose a Voice

Vapi supports multiple TTS providers:

  • ElevenLabs — Best quality, most natural (recommended)
  • PlayHT — Good quality, lower cost
  • Deepgram — Fast, good for real-time
  • Azure — Enterprise, many languages

2. Configure the Agent

{
  "name": "Appointment Setter",
  "firstMessage": "Hi! This is Sarah from Dr. Smith's office. I'm calling to help you schedule your appointment.",
  "systemPrompt": "You are Sarah, a friendly appointment scheduler...",
  "voice": {
    "provider": "11labs",
    "voiceId": "21m00Tcm4TlvDq8ikWAM"
  },
  "model": {
    "provider": "openai",
    "model": "gpt-4o",
    "temperature": 0.7
  },
  "endCallFunctionEnabled": true,
  "maxDurationSeconds": 300,
  "silenceTimeoutSeconds": 30
}

3. Prompt Engineering for Voice

Voice prompts differ from text. Key principles:

  • Keep responses SHORT — 1-2 sentences max per turn
  • Be conversational — use filler words naturally ("Sure thing!", "Got it!")
  • Handle interruptions — voice agents get cut off, design for it
  • Confirm understanding — repeat back key info (names, numbers, dates)
  • Include fallback — "I didn't catch that, could you repeat?"

4. Phone Number Setup

# List available phone numbers
python3 {baseDir}/scripts/vapi_agent.py list-phones

# Buy a number (via Vapi dashboard or API)
# Import existing number (Twilio, Vonage)
python3 {baseDir}/scripts/vapi_agent.py import-phone '{"provider":"twilio","number":"+15551234567","twilioAccountSid":"AC...","twilioAuthToken":"..."}'

5. Call Handling

Outbound calls:

python3 {baseDir}/scripts/vapi_agent.py call '{"assistantId":"asst_xxx","phoneNumberId":"pn_xxx","customer":{"number":"+15551234567"}}'

Inbound: Assign agent to phone number in Vapi dashboard, or via API:

python3 {baseDir}/scripts/vapi_agent.py update-phone '{"id":"pn_xxx","assistantId":"asst_xxx"}'

Integration Patterns

Voice + CRM (GHL)

  1. Voice agent qualifies lead on call
  2. Use Vapi's serverUrl webhook to capture call data
  3. On call end → create/update GHL contact
  4. Move opportunity to appropriate pipeline stage
  5. Schedule follow-up if needed

Voice + Calendar Booking

  1. Agent checks availability via calendar API
  2. Uses function calling to book appointment
  3. Confirms date/time verbally
  4. Sends SMS confirmation after call

Voice + Knowledge Base

Upload documents to Vapi's knowledge base for RAG:

python3 {baseDir}/scripts/vapi_agent.py create-kb '{"name":"Product FAQ","files":["faq.pdf"]}'

Available Commands

python3 {baseDir}/scripts/vapi_agent.py create-agent '{...}'     # Create new agent
python3 {baseDir}/scripts/vapi_agent.py get-agent <id>            # Get agent details
python3 {baseDir}/scripts/vapi_agent.py list-agents               # List all agents
python3 {baseDir}/scripts/vapi_agent.py update-agent <id> '{...}' # Update agent
python3 {baseDir}/scripts/vapi_agent.py delete-agent <id>         # Delete agent
python3 {baseDir}/scripts/vapi_agent.py call '{...}'              # Make outbound call
python3 {baseDir}/scripts/vapi_agent.py get-call <id>             # Get call details
python3 {baseDir}/scripts/vapi_agent.py list-calls                # List all calls
python3 {baseDir}/scripts/vapi_agent.py list-phones               # List phone numbers
python3 {baseDir}/scripts/vapi_agent.py import-phone '{...}'      # Import phone number
python3 {baseDir}/scripts/vapi_agent.py update-phone '{...}'      # Update phone config

Credits

Built by M. Abidi | agxntsix.ai YouTube | GitHub Part of the AgxntSix Skill Suite for OpenClaw agents.

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