---

name: sql-performance-review description: Review and improve Databricks SQL queries for correctness, readability, and performance (joins, filters, aggregations, partition pruning). Use when someone pastes a SQL query, asks why it is slow, or requests a rewrite/optimization in Databricks SQL. license: Proprietary. For internal team use. compatibility: Designed for Databricks Assistant agent mode. Works best when the user provides the SQL query and (optionally) table names, row counts, or query profile details. metadata: author: your-team version: "1.0"

Databricks SQL performance review

Use this skill when optimizing or reviewing SQL in Databricks SQL.

What to ask for (only if missing)

Ask up to 3 questions total:

1. The query text (if not provided)
2. The table(s) involved + their sizes (rough order of magnitude) OR the query profile / execution plan
3. The desired result constraints (correctness, exactness, latency SLA)

If the user can’t provide sizes/plan, proceed with best-effort heuristics and call out assumptions.

Output format

Use the structure in assets/sql-review-output.md.

Checklist

Use references/sql-checklist.md to ensure you cover the common performance levers:

• predicate pushdown / partition pruning
• join strategy and join keys
• avoid SELECT *
• minimize shuffles / wide aggregations
• use correct data types and avoid implicit casts
• reduce data scanned (pre-filter, semi-joins, EXISTS)

Examples

User: “This query is slow in Databricks SQL. Can you optimize it?” (pastes query)
Assistant: Provide issues, suggestions, and a rewritten query, plus next steps (EXPLAIN, add ZORDER, etc.).

Edge cases

• If the query is logically wrong (duplicates from joins, missing filters), fix correctness first.
• If tables are Delta: suggest partitioning/ZORDER/OPTIMIZE only if it matches query patterns.
• If the user is in a governed environment: avoid suggestions that require elevated permissions unless noted.