What is the advantage of the Keyset pagination pattern included?

Keyset pagination (or seek-based pagination) is more scalable than OFFSET-based pagination because it doesn't require the database to skip over thousands of rows, making it much faster for large tables.

How does this skill help with database performance?

It provides optimized indexing strategies and pagination patterns like Keyset, which prevent performance degradation as datasets scale.

Does it support different SQL dialects?

The skill focuses on standard SQL patterns applicable to major engines like PostgreSQL, MySQL, and SQL Server, with specific focus on modern features like CTEs.

How does it handle SQL anti-patterns?

It identifies inefficient practices—such as using SELECT * or improper date filtering—and provides the optimized alternative to ensure query efficiency.

Can it help with advanced data analysis?

Yes, it includes detailed syntax for window functions like RANK(), LAG(), and LEAD(), which are essential for time-series and comparative analysis.

SQL Design Patterns

Name: SQL Design Patterns
Author: 0xDarkMatter

by0xDarkMatter

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Database Management

Provides a comprehensive reference for advanced SQL syntax, optimization strategies, and common query implementation patterns.

About

The SQL Patterns skill equips Claude with a specialized knowledge base for writing high-performance, maintainable database queries. It offers instant access to complex Common Table Expressions (CTEs), window function syntax, and sophisticated indexing strategies. By implementing this skill, developers can quickly generate code for analytical tasks like running totals, optimize join logic, choose the correct index types (B-tree, Hash, GIN), and adopt scalable pagination techniques that outperform traditional methods.

Key Features

4 GitHub stars
Proactive identification and remediation of common SQL anti-patterns
Detailed guidance on window functions for ranking, offsets, and running totals
Comprehensive reference for Common Table Expressions (CTEs) and chained query logic
Database indexing strategies including B-tree, Hash, GIN, and covering indexes
Scalable pagination patterns using Keyset and Offset/Limit methods

Use Cases

Building complex analytical reports using advanced window functions and chained CTEs
Implementing efficient data retrieval systems for applications with large datasets
Refactoring slow-running queries by applying modern indexing and join strategies

About

Key Features

4 GitHub stars
Proactive identification and remediation of common SQL anti-patterns
Detailed guidance on window functions for ranking, offsets, and running totals
Comprehensive reference for Common Table Expressions (CTEs) and chained query logic
Database indexing strategies including B-tree, Hash, GIN, and covering indexes
Scalable pagination patterns using Keyset and Offset/Limit methods

Use Cases

Building complex analytical reports using advanced window functions and chained CTEs
Implementing efficient data retrieval systems for applications with large datasets
Refactoring slow-running queries by applying modern indexing and join strategies