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sql-query

Build and execute complex SQL queries with joins, window functions, and CTEs.

5|Updated Apr 8, 2026
Search Tags:#analytics#sql#query-optimization#cte#joins#window-functions
One-click install
npx skills add https://github.com/JansenAnalytics/claudex --skill sql-query-jansenanalytics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sql-query
Source: https://github.com/JansenAnalytics/claudex/tree/main/skills/sql-query
Command: npx skills add https://github.com/JansenAnalytics/claudex --skill sql-query-jansenanalytics

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Builds and executes complex SQL queries for analytics, including advanced joins, window functions, CTEs, and aggregations, to reduce manual query work and improve accuracy.

Core Features & Use Cases

  • Advanced SQL construction: Join operations, window functions, and CTEs to derive insights from relational data.
  • Query optimization guidance: Patterns and templates to improve performance across PostgreSQL, MySQL, and SQLite.
  • Use Case: Create a report that combines sales fact data with dimension tables, applying windowed calculations and grouped aggregations.

Quick Start

Execute a ready-to-run SQL template against your database to generate a result set.

Frequently Asked Questions about sql-query

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

FAQPage Schema
How do I write complex SQL queries with window functions and CTEs for analytics?▼

Complex SQL queries for analytics are built using advanced joins, window functions, and CTEs to derive insights from relational data. This approach reduces manual query work and improves accuracy when creating reports that combine fact data with dimension tables.

What's the best way to optimize SQL queries across PostgreSQL, MySQL, and SQLite?▼

SQL query optimization is achieved through patterns and templates that improve performance across PostgreSQL, MySQL, and SQLite. Guidance is provided via included scripts to help structure joins, window functions, and aggregations more efficiently.

Can I use this SQL query builder for data transformation and reporting on relational databases?▼

Yes, SQL query construction applies to data analysis, reporting, and data transformation across relational databases. It implements core features for query composition, execution, validation, and basic optimization guidance to generate result sets.

How do I combine sales fact data with dimension tables using grouped aggregations?▼

Combining sales fact data with dimension tables requires advanced SQL join operations, windowed calculations, and grouped aggregations. Ready-to-run templates are included to construct these queries and execute them against your database to generate a result set.

Does this SQL analytics tool require any external dependencies or database connectors?▼

No external dependencies are required to use the SQL query composition and execution features. The tool includes scripts and reference templates that handle validation and basic optimization guidance without needing additional packages.

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