quickstart

To set up a Databricks agent development environment, this Skill creates local authentication and MLflow configuration files automatically. It generates a `.env` with your Databricks CLI profile, MLflow tracking URI, and experiment ID, while updating `databricks.yml` for the ResponsesAgent workflow.

Configuring Databricks authentication requires verifying specific tool prerequisites. You must have `uv`, Node 20, and the Databricks CLI installed on your system before generating the `.env` and MLflow configuration files.

Yes, environment setup supports safe re-runs with idempotent behavior. If configurations already exist, the Skill skips prompts and updates the `.env` and `databricks.yml` files without overwriting existing valid settings.

You can bind local MLflow configuration to an existing Databricks app by passing the `--app-name` parameter. This updates `databricks.yml` to link the bundle to your specified app and automatically sets the required experiment ID.

Yes, the quickstart process automatically creates an MLflow experiment in Databricks. It generates the experiment ID and writes it directly into your local `.env` file and `databricks.yml` configuration.

The best way to initialize Databricks MLflow tracking is running `uv run quickstart`. This command validates prerequisites, creates the `.env` with authentication variables, and configures the MLflow tracking URI idempotently.