
databricks-dabs
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.
- Installs
- 898
- Last 24h
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/databricks/databricks-agent-skills --skill databricks-dabs- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads databricks-dabs automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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
FAQ
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 https://github.com/databricks/databricks-agent-skills --skill databricks-dabs in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/databricks-dabs/ (personal) or .claude/skills/databricks-dabs/ (project).
Which AI agents can use databricks-dabs?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is databricks-dabs safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains databricks-dabs?
It is published by databricks in databricks/databricks-agent-skills. It has 898 recorded installs.
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