skills/codex/databricks-docs/SKILL.md
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-docs --- # Databricks Documentation Reference This skill provides access to the complete Databricks documentation index via llms.txt - use it as a **reference resource** to supplement other skills and inform your use of MCP tools. ## Role of This Skill This is a **reference skill**, not an action skill. Use it to: - Look up documentation when other skills don't cover a topic - Get authoritative guidance on Databr
npx skillsauth add frank-luongt/faos-skills-marketplace skills/codex/databricks-docsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill provides access to the complete Databricks documentation index via llms.txt - use it as a reference resource to supplement other skills and inform your use of MCP tools.
This is a reference skill, not an action skill. Use it to:
Always prefer using MCP tools for actions (execute_sql, create_or_update_pipeline, etc.) and load specific skills for workflows (databricks-python-sdk, spark-declarative-pipelines, etc.). Use this skill when you need reference documentation.
Fetch the llms.txt documentation index:
URL: https://docs.databricks.com/llms.txt
Use WebFetch to retrieve this index, then:
The llms.txt file is organized by category:
Scenario: User wants to create a Delta Live Tables pipeline
spark-declarative-pipelines skill for workflow patternscreate_or_update_pipeline MCP tool to actually create the pipelineScenario: User asks about an unfamiliar Databricks feature
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: -