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 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
npx skills add majiayu000/claude-skill-registry --skill antigravity-voice-agents --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 - voice-interfaces ## Patterns ### Speech-to-Speech Architecture Direct audio-to-audio processing for lowest latency ### Pipeline Architecture Separate STT → LLM → TTS for maximum control ### Voice Activity Detection Pattern Detect when user starts/stops speaking ## Anti-Patterns ### ❌ Ignoring Latency Budget ### ❌ Silence-Only Turn Detection ### ❌ Long Responses ## ⚠️ Sharp Edges | Issue | Severity | Solution | |-------|----------|----------| | Issue | critical | # Measure and budget latency for each component: |
- Capabilities
- Patterns
- Speech-to-Speech Architecture
- Pipeline Architecture
- Voice Activity Detection Pattern
- Anti-Patterns
- ❌ Ignoring Latency Budget
- ❌ Silence-Only Turn Detection
- ❌ Long Responses
- ⚠️ Sharp Edges
- Related Skills
What does the voice-agents skill do?
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
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill antigravity-voice-agents --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.