The body is lean: a quick-reference table, concise executable SQL examples, and brief guideline bullets, with no padding explaining concepts Claude already knows such as what SQL or Databricks is.

Every pattern is shown as complete, copy-paste-ready SQL (e.g. 'CREATE OR REPLACE PROCEDURE...', 'WITH RECURSIVE...', 'SELECT * FROM read_files(...)') with concrete syntax and options rather than pseudocode.

As a single-purpose SQL reference, each action is unambiguous and the Key Guidelines include an explicit validation checkpoint ('Use MCP tools (execute_sql, execute_sql_multi) to test and validate all SQL before deploying'), which the rubric permits to score 3 for simple skills.

The body signals one-level-deep references in a well-organized table with clear 'When to Read' guidance, but the referenced files (sql-scripting.md, materialized-views-pipes.md, geospatial-collations.md, ai-functions.md, best-practices.md) do not exist in any bundle directory, so navigation points to missing files.

The description enumerates concrete capabilities such as 'SQL scripting', 'stored procedure', 'materialized view', 'pipe syntax', 'geospatial', 'collation', and 'AI functions', naming multiple specific actions rather than vague language.

It explicitly answers both 'what' (advanced DBSQL features and SQL warehouse capabilities) and 'when' via explicit triggers ('This skill MUST be invoked when the user mentions...', 'SHOULD also invoke when...').

It provides broad coverage of natural terms a user would actually say ('DBSQL', 'Databricks SQL', 'SQL warehouse', 'stored procedure', 'recursive CTE', 'ai_query'), including common variations and function-level keywords.

The niche is a clearly defined Databricks SQL domain with distinct, domain-specific triggers, making it unlikely to fire for unrelated skills.