Building a voice agent today usually means one of two things: either you hand everything over to a fully managed platform and lose control of your LLM, or you spend weeks stitching together speech-to-text, text-to-speech, turn detection, and interruption handling yourself. ElevenLabs just released a third option. Speech Engine is a new product that bolts a complete voice layer onto any existing chat agent, and the new Speech Engine Skill makes the setup a single terminal command.

One command to go from chat to voice

The ElevenLabs Skills repo is a collection of agent skills, which are structured folders of instructions and scripts that AI coding assistants like Cursor or Claude Code can load and execute. Installing the Speech Engine Skill looks like this:

npx skills add elevenlabs/skills

The skill sets up everything you need so you can go from chat to voice in a single prompt. The underlying Agent Skills format, defined at agentskills.io, works by progressively loading context into the coding assistant: only the skill name and description are loaded at startup, with full instructions pulled in only when the skill is actually needed. This keeps context usage minimal while still giving the LLM everything it needs to scaffold your integration correctly.

What Speech Engine actually does

ElevenLabs Speech Engine adds voice capabilities to any chat agent. ElevenLabs handles speech-to-text and text-to-speech while your server provides the LLM logic. The connection model is straightforward:

1. A user speaks in the browser. ElevenLabs captures the audio and transcribes it. The transcript is sent to your server along with the full conversation history.
2. Your server passes the transcript to your LLM and streams the response back.
3. ElevenLabs converts the text to speech and plays it in the browser.