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Agent skills are task-specific instruction files that AI coding assistants like Claude and GitHub Copilot can load to perform Azure Databricks development tasks. Skills package domain-specific knowledge, best practices, and workflows into a format optimized for AI consumption. To learn how to extend Genie Code in the Azure Databricks workspace, see Extend Genie Code with agent skills.
Skills follow the open Agent Skills standard. Each skill is a Markdown file with front-matter metadata that describes when and how the skill should be used. AI coding assistants automatically discover and load relevant skills based on the task at hand.
Install skills
Install skills using the Skills CLI, an open-source package manager for agent skills. The CLI scans a GitHub repository for skill files and installs them into your project so that your AI coding assistant can discover and use them automatically.
# List skills in a repository
npx skills add databricks/databricks-agent-skills --list
# Install specific skills
npx skills add databricks/databricks-agent-skills --skill databricks-apps --skill databricks-pipelines
# Install all skills from a repo to all agents
npx skills add databricks/databricks-agent-skills --all
# Remove interactively (select from installed skills)
npx skills remove
The CLI requires only that the repository contains skill files. Repository owners do not need to configure anything for the CLI to work with their skills.
Skill repositories
| GitHub repository | Description | Skills |
|---|---|---|
| Azure Databricks agent skills | Core skills for Azure Databricks CLI operations, app development, and pipeline authoring. | Azure Databricks CLI, app development, job orchestration, Lakebase, Spark Declarative Pipelines |
| Databricks app template skills | Skills embedded in Databricks app agent templates for building or migrating agents on Databricks Apps. | Agent deployment, agent migration, Model Serving to Databricks Apps migration, OpenAI Agents SDK, Azure Databricks Databricks Apps |
| AI Dev Kit skills | Curated community skills covering 25+ Azure Databricks development patterns. | SQL analytics, ML evaluation, model serving, streaming, pipelines, Unity Catalog, Lakebase, apps, and more |
| MLflow skills | Debugging, evaluating, and optimizing LLM agents | Tracing, LLM judges, evals, production traffic analysis |
Next steps
- Extend Genie Code with agent skills: Create skills for the built-in Genie Code in your workspace.
- Migrate an agent from Model Serving to Databricks Apps: Use agent skills to migrate an agent from Model Serving to Databricks Apps.
- Author an AI agent and deploy it on Databricks Apps: Build and deploy an AI agent on Databricks Apps.