
databricks-core
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.
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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-core- 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-core 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.
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-serverless - Compute choice for jobs and pipelines (serverless, performance mode, classic fallback)
- 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
-
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
UPGRADEorINSTALL: 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-localneeds 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_HOSTandDATABRICKS_TOKENenvironment variables if present in the shell. See the Databricks REST API docs.
- Run the floor check in CLI Installation. If it reports
-
Authenticated:
databricks auth profiles- If not: see CLI Authentication
Profile Selection - CRITICAL
NEVER auto-select a profile.
- List profiles:
databricks auth profiles - Present ALL profiles to user with workspace URLs
- Let user choose (even if only one exists)
- 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
| Error | Solution |
|---|---|
cannot configure default credentials | Use --profile flag or authenticate first |
configuration does not support OAuth tokens | The command requires OAuth (e.g., databricks apps logs). Re-authenticate with databricks auth login --host <URL> --profile <PROFILE>. See CLI Authentication. |
PERMISSION_DENIED | Check workspace/UC permissions |
RESOURCE_DOES_NOT_EXIST | Verify resource name/id and profile |
Required Reading by Task
| Task | READ BEFORE proceeding |
|---|---|
| First time setup | CLI Installation |
| Auth issues / new workspace | CLI Authentication |
| Exploring tables/schemas | Manual Data Exploration (or databricks-data-discovery if installed) |
| Deploying jobs/pipelines | Use /databricks-dabs |
Reference Guides
- CLI Installation
- CLI Authentication
- Manual Data Exploration
FAQ
What does the databricks-core skill do?
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.
How do I install databricks-core?
Run npx skills add https://github.com/databricks/databricks-agent-skills --skill databricks-core 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-core/ (personal) or .claude/skills/databricks-core/ (project).
Which AI agents can use databricks-core?
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-core 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-core?
It is published by databricks in databricks/databricks-agent-skills. It has 1,744 recorded installs.
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