Install Databricks Dabs
Pick your agent. Every command is ready to paste.
npx skills add databricks/databricks-agent-skills --skill databricks-dabsThe open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.
01
Install it
Run the command above, or upload the folder in Claude.
02
Ask naturally
Describe the task. Your agent loads databricks-dabs when the request matches its description.
03
Name it if needed
If it does not trigger, say “use the databricks-dabs skill”. In Codex, type $databricks-dabs.
Declarative Automation Bundles (DABs)
Use this skill for any bundle-related request including creating, configuring, validating, deploying, running, and managing Databricks resources through DABs.
Reference Documentation
The following reference files provide detailed guidance for specific bundle tasks:
- Bundle Structure - Bundle structure, databricks.yml configuration, resource definitions, path resolution, variables, and multi-environment targets
- SDP Pipelines - Spark Declarative Pipeline configurations for DABs
- SQL Alerts - SQL Alert schemas and configuration (critical - API differs from other resources)
- Deploy and Run - Validation, deployment, running resources, monitoring logs, and troubleshooting common issues
- Resource Permissions - Permission levels and access control for bundle resources, per-resource-type levels, grants vs permissions
When to Use This Skill
Load this skill for any request involving:
- Creating new bundle projects or resources
- Configuring databricks.yml or resource YAML files
- Setting up multi-environment deployments (dev/prod targets)
- Deploying or running bundle resources
- Managing permissions for bundle resources
- Troubleshooting bundle validation or deployment errors
- Working with specific resource types (dashboards, jobs, pipelines, alerts, volumes, apps)
General Guidelines
- Always validate after configuration changes - Use
bundle validate --strict --target <target>after any change - Use reference documentation - Consult the appropriate reference file for detailed patterns and examples
- Follow naming conventions - Resource files should use
<name>.<resource_type>.ymlformat - Path resolution is critical - Paths differ based on file location (see Bundle Structure reference)
- Preserve existing structure - Keep user comments and structure when editing YAML files
- Use variables - Parameterize catalog, schema, and warehouse for multi-environment support
- Namespace App names - App names are workspace-global and limited to 30 characters. With Databricks CLI 0.270.0 or later, shared-development defaults should include the app and
${workspace.current_user.domain_friendly_name}; override production with a stable name, and persist an explicit local value when the default is invalid, collides, or must distinguish multiple non-production targets in one workspace. On older CLI versions, require an explicitapp_namevalue instead
Required App Completion Contract
Before validating any bundle that creates or changes an App, re-read the final bundle YAML and confirm all of the following structural requirements:
- Each App resource uses a dedicated name variable, such as
name: ${var.app_name}, while preserving an existing equivalent variable when present. - For Databricks CLI 0.270.0 or later, each App name variable defaults to a recognizable App prefix plus
${workspace.current_user.domain_friendly_name}for development, and the production target overrides it with a stable name. On older CLI versions, App name variables have no default and each developer must provide values. - No development App name uses
${workspace.current_user.short_name}, a bare${bundle.target}, or a hardcoded value.
Only after this check, run databricks bundle validate --strict --target <target> --output json and inspect each resolved resources.apps.<key>.name. Each name must contain only lowercase letters, digits, and hyphens and be at most 30 characters. If a resolved name is invalid, collides after normalization, or multiple non-production targets share a workspace, persist a shorter, distinct value in the uncommitted .databricks/bundle/<target>/variable-overrides.json file and validate again. Successful validation alone does not satisfy this contract because validation does not catch every invalid or non-namespaced App name.
Documentation
- Declarative Automation Bundles
- Bundle Examples Repository - official end-to-end example bundles (jobs, pipelines, dashboards, apps, and more); use as working references for patterns not covered by the reference files above
Tips for Databricks Dabs
- • Start a fresh session after installing so your agent picks up the new skill.
- • It bundles reference files. The agent reads them only when needed, so they cost no context until then.
- • It is part of a pack with 30 skills. Install only the ones you need with --skill to keep triggers precise.
- • If two skills overlap, mention the one you want by name.
Questions about Databricks Dabs
What does the Databricks Dabs skill do?
Create, configure, validate, deploy, run, and manage Declarative Automation Bundles (DABs, formerly Databricks Asset Bundles). Use when working with Databricks resources via DABs including dashboards, jobs, pipelines, alerts, volumes, and apps.
How do I install Databricks Dabs?
Run "npx skills add databricks/databricks-agent-skills --skill databricks-dabs" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.
Does Databricks Dabs work in Cursor and Codex?
Yes. Databricks Dabs uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.
Is Databricks Dabs free?
Databricks Dabs is open source on GitHub. It is free to install; check the license before commercial use.
Who made Databricks Dabs?
Databricks Dabs is published by databricks in the databricks/databricks-agent-skills repository, together with 29 other skills.


