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Create and query Databricks Genie Spaces for natural language SQL exploration. Use when building Genie Spaces or asking questions via the Genie Conversation API.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Builds Python-based Databricks applications using Dash, Streamlit, Gradio, Flask, FastAPI, or Reflex. Handles OAuth authorization (app and user auth), app resources, SQL warehouse and Lakebase connectivity, model serving integration, and deployment. Use when building Python web apps, dashboards, ML demos, or REST APIs for Databricks, or when the user mentions Streamlit, Dash, Gradio, Flask, FastAPI, Reflex, or Databricks app.
Patterns and best practices for using Lakebase Provisioned (Databricks managed PostgreSQL) for OLTP workloads.
Patterns for Databricks Vector Search: create endpoints and indexes, query with filters, manage embeddings. Use when building RAG applications, semantic search, or similarity matching. Covers both storage-optimized and standard endpoints.
Use this when you need to EVALUATE OR IMPROVE or OPTIMIZE an existing LLM agent's output quality - including improving tool selection accuracy, answer quality, reducing costs, or fixing issues where the agent gives wrong/incomplete responses. Evaluates agents systematically using MLflow evaluation with datasets, scorers, and tracing. Covers end-to-end evaluation workflow or individual components (tracing setup, dataset creation, scorer definition, evaluation execution).
Instruments Python and TypeScript code with MLflow Tracing for observability. Triggers on questions about adding tracing, instrumenting agents/LLM apps, getting started with MLflow tracing, or tracing specific frameworks (LangGraph, LangChain, OpenAI, DSPy, CrewAI, AutoGen). Examples - "How do I add tracing?", "How to instrument my agent?", "How to trace my LangChain app?", "Getting started with MLflow tracing", "Trace my TypeScript app"
| name | databricks-genie |
| description | Create and query Databricks Genie Spaces for natural language SQL exploration. Use when building Genie Spaces or asking questions via the Genie Conversation API. |
Create and query Databricks Genie Spaces - natural language interfaces for SQL-based data exploration.
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.
Use this skill when:
| Tool | Purpose |
|---|---|
create_or_update_genie | Create or update a Genie Space |
get_genie | Get space details (by ID) or list all spaces (no ID) |
delete_genie | Delete a Genie Space |
| Tool | Purpose |
|---|---|
ask_genie | Ask a question or follow-up (conversation_id optional) |
| Tool | Purpose |
|---|---|
get_table_details | Inspect table schemas before creating a space |
execute_sql | Test SQL queries directly |
Before creating a Genie Space, understand your data:
get_table_details(
catalog="my_catalog",
schema="sales",
table_stat_level="SIMPLE"
)
create_or_update_genie(
display_name="Sales Analytics",
table_identifiers=[
"my_catalog.sales.customers",
"my_catalog.sales.orders"
],
description="Explore sales data with natural language",
sample_questions=[
"What were total sales last month?",
"Who are our top 10 customers?"
]
)
ask_genie(
space_id="your_space_id",
question="What were total sales last month?"
)
# Returns: SQL, columns, data, row_count
1. Inspect tables → get_table_details
2. Create space → create_or_update_genie
3. Query space → ask_genie (or test in Databricks UI)
4. Curate (optional) → Use Databricks UI to add instructions
Before creating a Genie Space:
Use these skills in sequence:
databricks-synthetic-data-generation - Generate raw parquet filesdatabricks-spark-declarative-pipelines - Create bronze/silver/gold tables| Issue | Solution |
|---|---|
| No warehouse available | Create a SQL warehouse or provide warehouse_id explicitly |
| Poor query generation | Add instructions and sample questions that reference actual column names |
| Slow queries | Ensure warehouse is running; use OPTIMIZE on tables |