> ## Documentation Index
> Fetch the complete documentation index at: https://docs.egma.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Text connections and Env

First [connect your LiveKit agent](/docs/integrations/livekit/connect) and prepare its worker.

## Add a text connection

Text mode tests conversation logic without the speech stack. First configure
your worker's text input and transcription output using the chat example in
the [Python SDK](/skills-cli-sdks/sdks/livekit-python#test-in-chat-mode) or
[JavaScript SDK](/skills-cli-sdks/sdks/livekit-javascript#test-in-chat-mode) guide. In rooms whose names
start with `egma-sim-chat-`, disable audio input and output. Keep any separate
greeting or audio publisher off in that mode.

Then add a second connection:

```bash theme={"system"}
egma agent connection add \
  --agent "$EGMA_AGENT_ID" \
  --access livekit-project-credentials \
  --modality chat \
  --livekit-url "$LIVEKIT_URL" \
  --livekit-agent-name "$LIVEKIT_AGENT_NAME" \
  --name "LiveKit text"
```

Use this connection's ID when starting a text run. The same suite can run
against either connection.

## Pass data to a test

If your worker reads startup context from `ctx.job.metadata`, put that context
in the test's `## Env` section:

````markdown theme={"system"}
## Env

```json
{
  "job_dispatch_metadata": {
    "tenant": "oak-street",
    "locale": "en-US"
  }
}
```
````

Use the exact keys your worker reads. Egma serializes this object as the
dispatch metadata string. Your normal `JSON.parse` or `json.loads` call reads
it in the worker. A test without this field receives empty dispatch metadata.
Egma does not add scenario instructions or other Egma fields to it.

To detect a simulation, check whether the room name starts with `egma-sim-`.
This includes text rooms. Keep that prefix reserved for Egma when your own
application creates production rooms.