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Run a real-time AI phone agent using Twilio, Deepgram, and ElevenLabs. Handles incoming calls, transcribes audio, generates responses via LLM, and speaks back via streaming TTS.
Passed 19 of 22 test cases with the skill, and 6 of 22 without it.
and 16 more in the full report
13 fixed6 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
What primary language model is configured out of the box for conversational logic in the script?
| Checked | Without skill | With skill |
|---|---|---|
| Names gpt-4o-mini as the default model | Missed | Passed |
The instructions your model reads when the skill loads.
Runs a local FastAPI server that acts as a real-time voice bridge.
Twilio (Phone) <--> WebSocket (Audio) <--> [Local Server] <--> Deepgram (STT)
|
+--> OpenAI (LLM)
+--> ElevenLabs (TTS)
Install Dependencies:
pip install -r scripts/requirements.txt
Set Environment Variables (in ~/.moltbot/.env, ~/.clawdbot/.env, or export):
export DEEPGRAM_API_KEY="your_key"
export OPENAI_API_KEY="your_key"
export ELEVENLABS_API_KEY="your_key"
export TWILIO_ACCOUNT_SID="your_sid"
export TWILIO_AUTH_TOKEN="your_token"
export PORT=8080
Start the Server:
test cases passed, vs 6 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.