voice-agents
221
总安装量
220
周安装量
#1236
全站排名
安装命令
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill voice-agents
Agent 安装分布
claude-code
177
opencode
161
gemini-cli
152
codex
120
cursor
117
Skill 文档
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 (STTâLLMâTTS) 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 â LLM â TTS for maximum control
Voice Activity Detection Pattern
Detect when user starts/stops speaking
Anti-Patterns
â Ignoring Latency Budget
â Silence-Only Turn Detection
â Long Responses
â ï¸ Sharp Edges
| Issue | Severity | Solution |
|---|---|---|
| Issue | critical | # Measure and budget latency for each component: |
| Issue | high | # Target jitter metrics: |
| Issue | high | # Use semantic VAD: |
| Issue | high | # Implement barge-in detection: |
| Issue | medium | # Constrain response length in prompts: |
| Issue | medium | # Prompt for spoken format: |
| Issue | medium | # Implement noise handling: |
| Issue | medium | # Mitigate STT errors: |
Related Skills
Works well with: agent-tool-builder, multi-agent-orchestration, llm-architect, backend