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sql-queries

Provide SQL syntax and functions for multiple warehouse dialects.

Updated Apr 3, 2026
Search Tags:#query optimization#data analysis#sql#data warehouse#database administration
One-click install
npx skills add https://github.com/jmolz/m0lz.02 --skill sql-queries-jmolz
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sql-queries
Source: https://github.com/jmolz/m0lz.02/tree/main/.agents/skills/sql-queries
Command: npx skills add https://github.com/jmolz/m0lz.02 --skill sql-queries-jmolz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides comprehensive SQL query guidelines and optimizations for multiple data warehouse dialects, streamlining query writing and performance tuning.

Core Features & Use Cases

  • Dialect-Specific References: Offers detailed syntax and function examples for Snowflake, BigQuery, Databricks, PostgreSQL, Redshift, and Databricks SQL.
  • Common SQL Patterns: Demonstrates practical patterns such as window functions, CTEs, cohort retention, funnel analysis, and deduplication.
  • Performance Tips: Provides guidelines for query optimization, indexing strategies, and performance monitoring.

Quick Start

Use the sql-queries skill to generate a date arithmetic query example for PostgreSQL.

Frequently Asked Questions about sql-queries

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write SQL queries for different data warehouse dialects like Snowflake and BigQuery?▼

To write SQL queries across data warehouse dialects, this Skill provides detailed syntax and function examples for Snowflake, BigQuery, Databricks, PostgreSQL, and Redshift, streamlining query writing and performance tuning.

What SQL patterns are available for cohort retention and funnel analysis?▼

For cohort retention and funnel analysis, this Skill demonstrates practical SQL patterns including window functions, CTEs, and deduplication techniques to streamline complex data analysis workflows.

What are the best ways to optimize SQL query performance in a data warehouse?▼

To optimize SQL query performance, this Skill provides guidelines for query optimization, indexing strategies, and performance monitoring tailored to specific data warehouse dialects.

Can I debug SQL syntax errors for PostgreSQL and Redshift using this Skill?▼

Yes, you can debug SQL syntax errors for PostgreSQL and Redshift. This Skill assists in query writing, optimization, and debugging by providing detailed dialect-specific syntax and function references.

Does this Skill support date arithmetic query generation for PostgreSQL?▼

Yes, this Skill supports date arithmetic query generation for PostgreSQL. You can use it to quickly generate specific SQL syntax examples and validate query logic for your data warehouse dialect.

When should I use CTEs versus window functions for data analysis?▼

When performing data analysis, this Skill provides references for both CTEs and window functions. It demonstrates practical SQL patterns to help you choose the right approach for deduplication, funnel analysis, and complex transformations.

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