skills.rest
mattmacleod16-svg
mattmacleod16-svgCOMMUNITY
Explore all skills by this author →
GitHub

sql-queries

Translate and optimize SQL queries across Snowflake, BigQuery, Databricks, and PostgreSQL.

1|Updated Feb 25, 2026
Search Tags:#performance#postgresql#sql#bigquery#dialects#data-warehouses
One-click install
npx skills add https://github.com/mattmacleod16-svg/freedomforge-max --skill sql-queries-mattmacleod16-svg
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sql-queries
Source: https://github.com/mattmacleod16-svg/freedomforge-max/tree/main/.agents/skills/sql-queries
Command: npx skills add https://github.com/mattmacleod16-svg/freedomforge-max --skill sql-queries-mattmacleod16-svg

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Resolve the challenge of writing correct, high-performance SQL across multiple data warehouse dialects.

Core Features & Use Cases

  • Cross-dialect SQL authoring: produce portable queries that run on Snowflake, BigQuery, Databricks, PostgreSQL, and more.
  • Dialect-aware optimization: apply performance patterns like window functions, CTEs, and aggregations to optimize execution.
  • Translation & modernization: translate legacy SQL across dialects and modernize queries for analytics workloads.

Quick Start

Translate and optimize a cross-dialect SQL query to run efficiently on Snowflake, BigQuery, Databricks, and 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 portable SQL queries that work across Snowflake, BigQuery, and PostgreSQL?▼

Portable SQL queries use dialect-aware syntax handling and reusable templates with standard CTEs, window functions, and aggregations to execute correctly across Snowflake, BigQuery, Databricks, and PostgreSQL platforms.

What is the best way to convert SQL queries between different data warehouse dialects?▼

Converting SQL between data warehouse dialects requires dialect-aware syntax translation to modernize legacy queries and ensure compatibility when moving analytics workloads across platforms like Snowflake, BigQuery, and Databricks.

How do I optimize slow SQL performance in BigQuery or Snowflake using CTEs and window functions?▼

Optimizing slow SQL performance in BigQuery or Snowflake involves applying dialect-aware performance patterns like window functions, CTEs, and aggregations to streamline execution plans and reduce query latency.

Does this approach support building analytics queries with window functions across multiple databases?▼

Yes, building analytics queries with window functions is supported across multiple databases by using dialect-aware syntax handling to ensure correct execution and high performance on various data warehouse platforms.

When should I not use portable SQL templates for data warehouse queries?▼

You should avoid portable SQL templates when a specific data warehouse platform offers unique, non-standard performance optimizations or proprietary functions that cannot be replicated using standard CTEs or window functions.

Related Skills

Explore More Data & Analytics Skills→
cy-walicy-wali

write-query

Translate natural-language data needs into dialect-specific optimized SQL queries.

Community
Intermediate
borgheiborghei
467

data-analyst

Query SQL databases, create visualizations, and generate insights reports.

Community
Intermediate
dieu-donneedieu-donnee

sql-pro

Diagnose SQL performance issues by analyzing queries, plans, and schema structures.

Community
Advanced
timequitytimequity
6

warehouse-optimization

Optimize data warehouse queries and storage across Snowflake, BigQuery, and Redshift.

Official
Intermediate