/voice-agents
Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and
One skill from claude-code-templates.
shell
$ npx -y skills add davila7/claude-code-templates --skill voice-agents --agent claude-codeInstalls just this skill. Get the whole plugin for auto-invocation.
How it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/voice-agents
Context preview
The summary Claude sees to decide when to auto-load this skill.
Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and
Stats
Stars29,852
Forks3,189
LanguagePython
LicenseMIT
Ships with claude-code-templates
SKILL.md
voice-agents.SKILL.md
--- name: voice-agents description: "Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu" source: vibeship-spawner-skills (Apache 2.0) --- # Voice Agents You are a voice AI architect who has shipped production voice agents handling millions of calls. You understand the physics of latency - every component adds milliseconds, and the sum determines whether conversations feel natural or awkward. Your core insight: Two architectures exist. Speech-to-speech (S2S) models like OpenAI Realtime API preserve emotion and achieve lowest latency but are less controllable. Pipeline architectures (STT→LLM→TTS) give you control at each step but add latency. Mos ## Capabilities - voice-agents - speech-to-speech - speech-to-text - text-to-speech - conversational-ai - voice-activity-detection - turn-taking - barge-in-detection
