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databricks-core

databricks/databricks-agent-skills

Databricks CLI operations, authentication, and entry point for all Databricks agent skills.

What is databricks-core?

Core skill for Databricks CLI setup, authentication, profile management, and bundle operations. Load this first for any Databricks CLI task, then load product-specific skills (jobs, pipelines, apps, model serving) or databricks-data-discovery for data exploration and SQL generation.

  • Manage Databricks CLI authentication and profile selection
  • Execute bundle validation and deployment with target selection
  • List and inspect resources (apps, jobs, clusters, warehouses, pipelines, serving endpoints)
  • Discover table schemas, run ad-hoc SQL queries, and find default warehouses
  • Route to specialized product skills and data exploration tools

How to install databricks-core

npx skills add https://github.com/databricks/databricks-agent-skills --skill databricks-core
Prerequisites
  • Databricks CLI version >= 1.0.0 installed and current
  • Databricks workspace access with valid credentials
Claude Code
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How to use databricks-core

  1. 1.Run `databricks auth profiles` to list available authentication profiles
  2. 2.Select a profile from the list (do not auto-select)
  3. 3.Use `--profile <PROFILE>` flag with all CLI commands or set `DATABRICKS_CONFIG_PROFILE` environment variable
  4. 4.For data exploration, use `databricks experimental aitools tools discover-schema` or `databricks experimental aitools tools query`
  5. 5.Load a product-specific skill (databricks-jobs, databricks-pipelines, etc.) for specialized tasks

Use cases

Good for
  • Setting up CLI authentication for a new Databricks workspace
  • Selecting the correct profile before deploying jobs or pipelines
  • Exploring table structure and running quick SQL queries on Databricks data
  • Validating and deploying Databricks bundles to specific targets
  • Discovering available resources (clusters, warehouses, endpoints) in a workspace
Who it's for
  • Data engineers deploying Databricks jobs and pipelines
  • Data analysts exploring Databricks tables and running SQL queries
  • Platform engineers managing Databricks workspaces and bundles
  • Developers building full-stack apps on Databricks

databricks-core FAQ

Do I need to install the CLI separately?

Yes. The CLI must be version >= 1.0.0. Run the floor check in CLI Installation to verify; if it reports UPGRADE or INSTALL, follow that guide before proceeding.

How do I authenticate with Databricks?

Run `databricks auth profiles` to list profiles. If none exist, follow the CLI Authentication guide to create one using `databricks auth login`.

Why does my profile not persist between commands in Claude Code?

Each Bash command runs in a separate shell session. Use the `--profile` flag with every command, or chain commands with `&&` and set `DATABRICKS_CONFIG_PROFILE` in the same session.

What's the difference between this skill and databricks-data-discovery?

databricks-core handles CLI operations, authentication, and bundles. databricks-data-discovery specializes in finding tables, answering natural-language questions about data, and generating SQL via Genie One.

How do I list tables in a schema?

Use positional arguments: `databricks tables list <CATALOG> <SCHEMA> --profile <PROFILE>`. Do not use `--catalog` or `--schema` flags; they do not exist.

Full instructions (SKILL.md)

Source of truth, from databricks/databricks-agent-skills.


name: "databricks-core" description: "Databricks CLI operations and the parent/entry-point skill for Databricks CLI use: authentication, profile selection, and bundles. Load this first for CLI, auth, profile, and bundle tasks, then load the matching product skill. For finding or exploring data, answering questions about the data, or generating SQL, load the databricks-data-discovery skill (it routes to Genie One). Contains up-to-date guidelines for Databricks-related CLI tasks." compatibility: Requires databricks CLI (>= v1.0.0) metadata: version: "0.1.0"

Databricks

Core skill for Databricks CLI, authentication, and data exploration.

Product Skills

For specific products, use dedicated skills:

  • databricks-jobs - Lakeflow Jobs development and deployment
  • databricks-pipelines - Lakeflow Spark Declarative Pipelines (batch and streaming data pipelines)
  • databricks-apps - Full-stack TypeScript app development and deployment
  • databricks-lakebase - Lakebase Postgres Autoscaling project management
  • databricks-model-serving - Model Serving endpoint management and inference

For data discovery, exploration, and query generation — finding tables, answering natural-language questions about the data, or generating SQL — use databricks-data-discovery (it asks Genie One first, then falls back to manual exploration). If it isn't installed, use the AI-tool commands below and Manual Data Exploration.

Prerequisites

  1. CLI installed and current: the CLI must be >= v1.0.0. A CLI that is present but too old is not "good enough" — it must be upgraded, not worked around.

    • Run the floor check in CLI Installation. If it reports UPGRADE or INSTALL: STOP and follow that reference file to upgrade or install — do not proceed or tell the user their CLI is fine.
    • If another skill routed you here to upgrade (it needs a newer CLI than v1.0.0 — e.g. databricks-setup-local needs v1.16.0), that skill already detected the gap. A passing v1.0.0 floor check is not enough: follow the Update / repair procedures to install the latest stable, which satisfies any skill's floor.
    • Note: In sandboxed environments (Cursor IDE, containers), install commands write outside the workspace and may be blocked. Present the install command to the user and ask them to run it in their own terminal.
    • Exception: If CLI installation is blocked (sandboxed containers, restricted environments), ask the user whether to fall back to direct REST API calls using DATABRICKS_HOST and DATABRICKS_TOKEN environment variables if present in the shell. See the Databricks REST API docs.
  2. Authenticated: databricks auth profiles

Profile Selection - CRITICAL

NEVER auto-select a profile.

  1. List profiles: databricks auth profiles
  2. Present ALL profiles to user with workspace URLs
  3. Let user choose (even if only one exists)
  4. Offer to create new profile if needed

Claude Code - IMPORTANT

Each Bash command runs in a separate shell session.

# WORKS: --profile flag
databricks apps list --profile my-workspace

# WORKS: chained with &&
export DATABRICKS_CONFIG_PROFILE=my-workspace && databricks apps list

# DOES NOT WORK: separate commands
export DATABRICKS_CONFIG_PROFILE=my-workspace
databricks apps list  # profile not set!

Data Exploration — Use AI Tools

Use these instead of manually navigating catalogs/schemas/tables:

# discover table structure (columns, types, sample data, stats)
databricks experimental aitools tools discover-schema catalog.schema.table --profile <PROFILE>

# run ad-hoc SQL queries
databricks experimental aitools tools query "SELECT * FROM table LIMIT 10" --profile <PROFILE>

# find the default warehouse
databricks experimental aitools tools get-default-warehouse --profile <PROFILE>

Names are literal. Use catalog/schema/table names exactly as given — never change a hyphen to an underscore or otherwise normalize them. In SQL, backtick-quote any name part with special characters (e.g. `my-catalog`.schema.table); unquoted hyphens cause a parse error.

These commands are first-class for running known SQL and profiling — Genie isn't required for that. For natural-language data questions, locating data you can't pin down, or generating a query from a question, prefer the databricks-data-discovery skill (above) if it's installed. See Manual Data Exploration for the full command surface, quoting rules, and troubleshooting.

Quick Reference

⚠️ CRITICAL: Some commands use positional arguments, not flags

# current user
databricks current-user me --profile <PROFILE>

# list resources
databricks apps list --profile <PROFILE>
databricks jobs list --profile <PROFILE>
databricks clusters list --profile <PROFILE>
databricks warehouses list --profile <PROFILE>
databricks pipelines list --profile <PROFILE>
databricks serving-endpoints list --profile <PROFILE>

# ⚠️ Unity Catalog — POSITIONAL arguments (NOT flags!)
databricks catalogs list --profile <PROFILE>

# ✅ CORRECT: positional args
databricks schemas list <CATALOG> --profile <PROFILE>
databricks tables list <CATALOG> <SCHEMA> --profile <PROFILE>
databricks tables get <CATALOG>.<SCHEMA>.<TABLE> --profile <PROFILE>

# ❌ WRONG: these flags/commands DON'T EXIST
# databricks schemas list --catalog-name <CATALOG>    ← WILL FAIL
# databricks tables list --catalog <CATALOG>           ← WILL FAIL
# databricks sql-warehouses list                       ← doesn't exist, use `warehouses list`
# databricks execute-statement                         ← doesn't exist, use `experimental aitools tools query`
# databricks sql execute                               ← doesn't exist, use `experimental aitools tools query`

# When in doubt, check help:
# databricks schemas list --help

# get details
databricks apps get <NAME> --profile <PROFILE>
databricks jobs get --job-id <ID> --profile <PROFILE>
databricks clusters get --cluster-id <ID> --profile <PROFILE>

# bundles
databricks bundle init --profile <PROFILE>
databricks bundle validate --profile <PROFILE>
databricks bundle deploy -t <TARGET> --profile <PROFILE>
databricks bundle run <RESOURCE> -t <TARGET> --profile <PROFILE>

Troubleshooting

ErrorSolution
cannot configure default credentialsUse --profile flag or authenticate first
configuration does not support OAuth tokensThe command requires OAuth (e.g., databricks apps logs). Re-authenticate with databricks auth login --host <URL> --profile <PROFILE>. See CLI Authentication.
PERMISSION_DENIEDCheck workspace/UC permissions
RESOURCE_DOES_NOT_EXISTVerify resource name/id and profile

Required Reading by Task

TaskREAD BEFORE proceeding
First time setupCLI Installation
Auth issues / new workspaceCLI Authentication
Exploring tables/schemasManual Data Exploration (or databricks-data-discovery if installed)
Deploying jobs/pipelinesUse /databricks-dabs

Reference Guides