skills/codex/databricks-config/SKILL.md
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-config --- Configure the Databricks profile in ~/.databrickscfg for use with Databricks Connect. **Usage:** `/databricks-config [profile_name|workspace_host]` Examples: - `/databricks-config` - Configure DEFAULT profile (interactive) - `/databricks-config DEFAULT` - Configure DEFAULT profile - `/databricks-config my-workspace` - Configure profile named "my-workspace" - `/databricks-config https://adb-1234567890123
npx skillsauth add frank-luongt/faos-skills-marketplace skills/codex/databricks-configInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Configure the Databricks profile in ~/.databrickscfg for use with Databricks Connect.
Usage: /databricks-config [profile_name|workspace_host]
Examples:
/databricks-config - Configure DEFAULT profile (interactive)/databricks-config DEFAULT - Configure DEFAULT profile/databricks-config my-workspace - Configure profile named "my-workspace"/databricks-config https://adb-1234567890123456.7.azuredatabricks.net/ - Configure using
workspace host URLDetermine the profile and host:
https://, treat it as a workspace host:
adb-1234567890123456.7.azuredatabricks.net →
adb-1234567890123456, my-company-dev.cloud.databricks.com → my-company-dev)https://, treat it as a profile nameRun databricks auth login -p <profile> with the determined profile name
--host <workspace_host> to the commandCheck if the profile exists in ~/.databrickscfg
Ask the user to choose ONE of the following compute options:
serverless_compute_id = auto)Update the profile in ~/.databrickscfg with the selected configuration
Verify the configuration by displaying the updated profile section
cluster_id OR serverless_compute_id (never both)serverless_compute_id = auto (not just serverless = true)databricks auth login command will open a browser for OAuth authenticationtoken field values (e.g., token = [REDACTED])~/.databrickscfgWith Cluster ID:
[DEFAULT]
host = https://adb-123456789.11.azuredatabricks.net/
cluster_id = 1217-064531-c9c3ngyn
auth_type = databricks-cli
With Serverless:
[DEFAULT]
host = https://adb-123456789.11.azuredatabricks.net/
serverless_compute_id = auto
auth_type = databricks-cli
With Token (display as redacted):
[DEFAULT]
host = https://adb-123456789.11.azuredatabricks.net/
token = [REDACTED]
cluster_id = 1217-064531-c9c3ngyn
View full configuration at: ~/.databrickscfg
<!-- Source: .faos/custom/skills/cloud/databricks/databricks-config/SKILL.md -->development
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-mlflow-evaluation --- # MLflow 3 GenAI Evaluation ## Before Writing Any Code 1. **Read GOTCHAS.md** - 15+ common mistakes that cause failures 2. **Read CRITICAL-interfaces.md** - Exact API signatures and data schemas ## End-to-End Workflows Follow these workflows based on your goal. Each step indicates which reference files to read. ### Workflow 1: First-Time Evaluation Setup For users new to MLflow GenAI evalu
development
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-lakebase-provisioned --- # Lakebase Provisioned Patterns and best practices for using Lakebase Provisioned (Databricks managed PostgreSQL) for OLTP workloads. ## When to Use Use this skill when: - Building applications that need a PostgreSQL database for transactional workloads - Adding persistent state to Databricks Apps - Implementing reverse ETL from Delta Lake to an operational database - Storing chat/agent m
tools
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-jobs --- # Databricks Lakeflow Jobs ## Overview Databricks Jobs orchestrate data workflows with multi-task DAGs, flexible triggers, and comprehensive monitoring. Jobs support diverse task types and can be managed via Python SDK, CLI, or Asset Bundles. ## Reference Files | Use Case | Reference File | | ----------------------
development
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-genie --- # Databricks Genie Create and query Databricks Genie Spaces - natural language interfaces for SQL-based data exploration. ## Overview Genie Spaces allow users to ask natural language questions about structured data in Unity Catalog. The system translates questions into SQL queries, executes them on a SQL warehouse, and presents results conversationally. ## When to Use This Skill Use this skill when: -