Create Voice Agent
SkillCloud & infraLets your agent build, fix, and improve real-time voice agents that listen and speak using NVIDIA tools.
Then ask your AI: use the Create Voice Agent skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add it as a step in a pipeline you build on Ahel, or connect Ahel to Claude, ChatGPT, Cursor, Claude Code or Codex and ask your AI to use it.
About this skill
Create, refine, or fix NVIDIA voice agents (Cascaded or Omni) with Pipecat or LiveKit. Use when building, scaffolding, or iterating on a real-time voice-agent pipeline, including speech (ASR/TTS) customization and cloud or local deployment. Not for offline/batch speech-to-text, text-only chat or RAG
What this skill tells your AI
The instructions your AI receives, as published by nvidia/skills in skills/nemotron-voice-agent-builder/SKILL.md and read by Ahel’s review.
Creates a working NVIDIA voice agent or updates an existing project:
- Cascaded: ASR transcribes, a text LLM answers, TTS speaks.
- Omni: one audio-in LLM replaces ASR and the text LLM. TTS still speaks.
When to Use This Skill
Use this skill when the user wants to build, scaffold, configure, refine, or fix an NVIDIA voice agent — a real-time speech pipeline with audio input and spoken output — on Pipecat or LiveKit. This covers Cascaded (ASR → LLM → TTS) and Omni (audio-in LLM + TTS) pipelines, speech customization (ASR word boosting, TTS pronunciation), multilingual routing, and cloud or local deployment (NIM, vLLM, NeMo-Speech.cpp) on workstations, DGX Spark, or Jetson Thor.
Do not use this skill for text-only chatbots or RAG, standalone batch speech-to-text transcription, generic Docker or infrastructure help, or unrelated CUDA or model work that has no voice-agent pipeline.
Workflow
Classify the starting state before following the phases:
- For an empty project, follow all phases in order.
- For a working existing project, read
references/operations/iterate.mdfirst, and then route only the references needed for the requested change. - For a broken existing project, read
references/operations/troubleshoot.mdfirst. After restoring the baseline, continue withreferences/operations/iterate.md.
For an empty project, follow these phases in order:
| Phase | Read |
|---|---|
| 1. Intake | references/intake.md resolves pipeline and framework first, then routes preflight, models, language, and domain files |
| 2. Build | references/platforms/readiness.md if self-hosted → exact profile or quantization variant in the routed model file → references/output-contract.md → routed deployment path → references/operations/observability.md → selected framework files |
| 3. Hand over | references/operations/run.md gates the client on the generated scripts/smoke.sh, then references/operations/troubleshoot.md if the spoken exchange fails |
| 4. Iterate | references/operations/iterate.md for changes to a working agent |
Wait for approval before writing files.
references/preflight.md §4 probes the host and selects the deployment path. The routed
platform file owns that path from there.
Also read references/networking/remote-webrtc.md when Pipecat WebRTC crosses hosts or
networks.
Rules
- Resolve every model id, image tag, profile, and serve flag from current NVIDIA documentation at build time. Never from memory.
- Read every routed file before generating code, and keep the language and behavior locks approved in intake.
- Handover requires a successful spoken exchange. A running process is not a working voice agent.
Signals
- GitHub stars
- 4k
- Forks
- 434
- Last commit
- Oct 2026
Ahel review
K3info
injection (in evals/evals.json)K3info
injection (in references/models/asr.md)
Automated review, not a security audit. Ruleset v1+k2.
Advanced
- Item type
- skill
- Key
nemotron-voice-agent-builder- Source
- github.com/nvidia/skills
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