Productivity

databricks

databricks/databricks-agent-skills · updated Apr 15, 2026

$npx skills add https://github.com/databricks/databricks-agent-skills --skill databricks
summary

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

skill.md

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

Prerequisites

  1. CLI installed: Run databricks --version to check.

    • If the CLI is missing or outdated (< v0.292.0): STOP. Do not proceed or work around a missing CLI.
    • Read the CLI Installation reference file and follow the instructions to guide the user through installation.
    • 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.
  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>

See Data Exploration for details.

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
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 Data Exploration
Deploying jobs/pipelines Declarative Automation Bundles

Reference Guides

general reviews

Ratings

4.562 reviews
  • James Tandon· Dec 28, 2024

    Registry listing for databricks matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Zaid Chawla· Dec 12, 2024

    We added databricks from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Ganesh Mohane· Dec 8, 2024

    Solid pick for teams standardizing on skills: databricks is focused, and the summary matches what you get after install.

  • Olivia Kapoor· Dec 8, 2024

    databricks has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Alexander Menon· Dec 4, 2024

    databricks reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Sakshi Patil· Nov 27, 2024

    We added databricks from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Camila Abebe· Nov 27, 2024

    databricks fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Amelia Rao· Nov 23, 2024

    I recommend databricks for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Zaid Torres· Nov 19, 2024

    Useful defaults in databricks — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Liam Kapoor· Nov 11, 2024

    I recommend databricks for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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