Can this skill help improve query performance?

Yes, it enforces performance-first patterns such as early filtering (pushing WHERE clauses close to sources), using UNION ALL by default, and profiling queries with EXPLAIN ANALYZE.

Which database dialects does this skill support?

While the skill provides specific patterns for PostgreSQL and BigQuery, its core principles of clear structure, explicit columns, and performance optimization apply to most modern SQL dialects.

Does it follow specific formatting standards?

Yes, it adheres to clean formatting rules including uppercase keywords, explicit JOIN syntax, and trailing commas to ensure compatibility with linters like SQLFluff and clean git diffs.

How does it handle complex query logic?

The skill mandates the use of Common Table Expressions (CTEs) to break complex logic into named, logical units, making queries easier to read, debug, and test.

SQL Engineering

Name: SQL Engineering
Author: btimothy-har

bybtimothy-har

Database Management

Writes, optimizes, and structures high-performance SQL queries and database schemas tailored to specific dialects like PostgreSQL and BigQuery.

About

The SQL Engineering skill transforms Claude into a specialized database architect, ensuring all generated SQL is performant, readable, and maintainable. It enforces best practices such as utilizing Common Table Expressions (CTEs) for logical clarity, implementing robust NULL handling patterns, and applying dialect-specific optimizations for platforms like BigQuery and PostgreSQL. Whether you are designing complex schemas with GIN indexes and enums or refactoring legacy queries to improve execution plans, this skill provides the necessary constraints and patterns to maintain production-grade database code standards.

Key Features

Explicit NULL safety and three-valued logic handling
Dialect-aware query optimization for PostgreSQL and BigQuery
Schema design patterns with specialized indexing and data types
SQLFluff-compatible formatting including trailing commas and uppercase keywords
Advanced CTE structuring for modular and testable query logic
0 GitHub stars

Use Cases

Refactoring monolithic legacy queries into modular, CTE-based structures
Optimizing data warehouse costs in BigQuery through partitioning and early filtering
Designing performant database schemas with appropriate indexing and identity columns

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add btimothy-har/bworkspace sql

For use in Claude.ai and ChatGPT

Download Skill

GitHub