Tsql Master

Complete T-SQL function reference for SQL Server and Azure SQL Database. PROACTIVELY activate for: (1) string functions (CONCAT_WS, STRING_SPLIT, STRING_AGG, TRIM, REPLACE, LEFT/RIGHT/SUBSTRING), (2) date/time functions (DATEADD, DATEDIFF, FORMAT, DATETRUNC, AT TIME ZONE), (3) math and conversion functions (CAST, CONVERT, TRY_CAST, ROUND, FLOOR, CEILING), (4) window/ranking functions (ROW_NUMBER, RANK, LEAD/LAG, FIRST_VALUE, LAST_VALUE, NTILE), (5) JSON functions (JSON_VALUE, JSON_QUERY, JSON_MODIFY, OPENJSON), (6) XML functions (FOR XML, .nodes, .value), (7) aggregate functions and GROUP BY extensions, (8) system and metadata functions (sys.* views, OBJECT_ID, OBJECT_NAME). Provides: function catalog grouped by category, version-availability matrix (SQL 2016+/2019+/2022+), and worked examples for each function family.

This skill should be used when the user asks to design, review, add, drop, consolidate, or tune SQL Server indexes. PROACTIVELY activate for clustered vs nonclustered design, covering indexes and INCLUDE columns, filtered indexes, columnstore indexes, missing-index DMV interpretation, duplicate or unused indexes, index maintenance, fragmentation, fill factor, compression, partition-aligned indexes, partition elimination proof, huge-table index constraints, online/resumable rebuilds, and index changes for slow T-SQL queries. Provides: index-design decision tree, workload-aware tradeoff checklist, DMV interpretation guidance, and maintenance/rebuild patterns.

Advanced T-SQL patterns and techniques for SQL Server and Azure SQL. PROACTIVELY activate for: (1) writing CTEs and recursive queries, (2) APPLY operator (CROSS APPLY, OUTER APPLY), (3) MERGE statement and OUTPUT clause, (4) temporal tables (system-versioned), (5) In-Memory OLTP / memory-optimized tables, (6) advanced grouping (ROLLUP, CUBE, GROUPING SETS), (7) PIVOT and UNPIVOT, (8) ROW_NUMBER/RANK/DENSE_RANK with PARTITION BY, (9) hierarchies via recursive CTE or HierarchyId, (10) JSON_ARRAYAGG and STRING_AGG patterns. Provides: pattern catalog with examples for each technique, performance tradeoffs, and copy-pasteable templates for common advanced query shapes.

This skill should be used when the user asks to optimize slow T-SQL queries, fix SQL Server performance regressions, improve SARGability, rewrite joins, prove whether joins can be removed, compare temp-table data types, select rewrite templates, diagnose parameter sniffing, evaluate query hints, inspect statistics/cardinality estimates, reduce spills or memory grants, use Query Store, or interpret plan evidence. PROACTIVELY activate for slow queries, scans vs seeks, implicit conversions, bad joins, tempdb spills, query rewrites, partition predicate safety, and before recommending indexes or hints. Provides: evidence-first workflow, rewrite templates, parameter-sniffing playbook, and gating rules before recommending indexes or hints.

Azure SQL Database optimization and platform-specific features. PROACTIVELY activate for: (1) Azure SQL Database optimization, (2) DTU vs vCore selection and right-sizing, (3) automatic tuning (force last good plan, create/drop index), (4) Hyperscale tier and read replicas, (5) Serverless tier and auto-pause, (6) Azure SQL performance monitoring (Query Performance Insight, Intelligent Insights), (7) elastic pools, (8) Always Encrypted with secure enclaves, (9) Managed Instance vs Azure SQL DB tradeoffs, (10) failover groups and geo-replication. Provides: tier-selection matrix, automatic-tuning enablement steps, Hyperscale architecture overview, monitoring queries, and elastic pool sizing guidance.

This skill should be used when the user asks to analyze SQL Server execution plans, .sqlplan files, ShowPlan XML, actual vs estimated plans, plan warnings, or operator costs. PROACTIVELY activate for: .sqlplan triage, ShowPlan XML inspection, high-cost operator ranking, scan vs seek review, residual predicate analysis, CONVERT_IMPLICIT warnings, bad row estimates, cardinality-estimation warnings, partition elimination verification, missing-index suggestions, unused-index warnings, spills, key lookups, sorts, hash joins, and plan-regression evidence gathering. Provides: plan triage workflow, operator-cost ranking heuristics, warning interpretation rubric, and rewrite/index recommendation gating.