A Databricks SQL reference router for advanced queries, warehouse capabilities and version-sensitive features.
Editorial review checked 2026-10-29 against this instruction snapshot. Supporting scripts and runtime behavior remain outside this editorial review.
The source covers SQL scripting, procedures, materialized views, federation, geospatial work and selected AI or HTTP functions. It points to detailed references rather than implying that all syntax works on every runtime. Development limits and warehouse selection are part of its operational guidance.
Developers extending an existing DBSQL workflow beyond basic selects and needing the relevant feature reference.
Some functions access external services or invoke paid models. Serverless and runtime prerequisites can differ by feature. A query that parses can still be expensive, reveal data or use the wrong aggregation, so access and cost require review before execution.
Requires databricks CLI (>= v1.0.0)
Inspect the pinned source snapshot and its supporting files first. The command selects this skill through the open-source skills CLI. Node.js and agent-specific setup may be required. Installation can download code; this catalog never runs it.
npx skills add https://github.com/databricks/databricks-agent-skills/tree/d50672205671c6d6edc847b1ddc36e7cba69bd32/skills/databricks-dbsql --skill databricks-dbsqlReview pinned skill folder ↗ · CLI documentation ↗
After source review, use npx skills check and npx skills update to inspect and apply upstream updates. Re-check changed instructions before running them.
Static review only. This is not a security audit or a guarantee of safety.
SKILL.md text only; scripts, dependencies and runtime behavior not audited.
Allowed tools declaration: Unknown. Runtime permissions and network behavior: Unknown.
74/100 · Metadata coverage 80% · Model 1.0
Scores summarize observable discovery signals. Popularity and repository activity apply to the whole repository. Unknown runtime safety earns no certification.
Identify the exact feature and warehouse context, inspect its current reference and test against a bounded nonproduction dataset. Keep external calls and AI functions explicit rather than incidental to a larger query.
Check result correctness, execution plan, scanned volume and effective permissions. Exercise failure handling for procedures or external calls, confirm actual supported versions and document any ongoing refresh or model-inference costs before scheduling the workload.
Related by category; compare scope and dependencies before choosing an alternative.
Explore 360 feedback system as a data & databases workflow from sickn33/agentic-awesome-skills. Compare its source, maintenance and review signals before choosing it for your agent.
Explore access matrix as a data & databases workflow from sickn33/agentic-awesome-skills. Compare its source, maintenance and review signals before choosing it for your agent.
Explore adhx as a data & databases workflow from sickn33/agentic-awesome-skills. Compare its source, maintenance and review signals before choosing it for your agent.
Explore databricks ai functions as a ai & machine learning workflow from databricks/databricks-agent-skills. Compare its source, maintenance and review signals before choosing it for your agent.
Explore databricks ai runtime as a ai & machine learning workflow from databricks/databricks-agent-skills. Compare its source, maintenance and review signals before choosing it for your agent.
Explore databricks aibi dashboards as a testing & qa workflow from databricks/databricks-agent-skills. Compare its source, maintenance and review signals before choosing it for your agent.