Voice Agents

SkillMedia

voice-agents is a skill that guides your agent through building apps that let people talk to AI by voice. It covers the full loop of speech recognition, synthesis, and conversation flow, including handling interruptions, background noise, and emotional nuance. The focus is on achieving natural back-and-forth dialogue with low latency.

Use Voice Agents in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add Voice Agents and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use the Voice Agents skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Ensure your agent environment supports skill installation.

Voice AgentsStart free

What your AI can do with it

  • Guide building voice apps with speech recognition and synthesis
  • Handle interruptions during spoken conversation
  • Manage background noise in voice interactions
  • Address emotional nuance in speech
  • Target sub-800ms latency for natural flow

Getting started

  1. Ensure your agent environment supports skill installation.
  2. Add the voice-agents skill to your agent's configuration.
  3. Provide the skill with access to speech recognition and synthesis tools.
  4. Start a project that involves voice interaction and follow the skill's guidance.

What this skill tells your AI

The instructions your AI receives, as published by davila7/claude-code-templates in cli-tool/components/skills/ai-research/voice-agents/SKILL.md and read by ahel’s review.

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

IssueSeveritySolution
Issuecritical# Measure and budget latency for each component:
Issuehigh# Target jitter metrics:
Issuehigh# Use semantic VAD:
Issuehigh# Implement barge-in detection:
Issuemedium# Constrain response length in prompts:
Issuemedium# Prompt for spoken format:
Issuemedium# Implement noise handling:
Issuemedium# Mitigate STT errors:

Related Skills

Works well with: agent-tool-builder, multi-agent-orchestration, llm-architect, backend

Signals

GitHub stars
32k
Forks
4k
Last commit
Oct 2026

Questions

What is voice-agents?
It is a skill that guides your agent through building apps that let people talk to AI by voice, covering speech recognition, synthesis, and natural conversation flow.
What kind of tool is voice-agents?
It is a skill, a set of instructions your agent can use to help you build voice-enabled applications.
What does voice-agents help with?
It helps with building apps where humans speak naturally with AI, including handling interruptions, background noise, and emotional nuance.
Does voice-agents require specific speech tools?
The skill assumes access to speech recognition and synthesis tools, but does not name specific providers.
Advanced
Item type
skill
Key
voice-agents
Source
github.com/davila7/claude-code-templates