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sql-queries

Convert natural language data requests into executable SQL queries.

2|Updated Apr 9, 2026
Search Tags:#database#data-analysis#query-optimization#sql-generation#schema-analysis#multi-dialect
One-click install
npx skills add https://github.com/skytiger6724/qwen-skills --skill sql-queries-skytiger6724
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sql-queries
Source: https://github.com/skytiger6724/qwen-skills/tree/main/sql-queries
Command: npx skills add https://github.com/skytiger6724/qwen-skills --skill sql-queries-skytiger6724

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill eliminates guesswork by turning natural language data questions into precise SQL, so analysts can act fast without wrestling with dialects or schema details.

Core Features & Use Cases

  • Dialect-aware query writing: Generates BigQuery, PostgreSQL, MySQL, Snowflake, and SQL Server code tailored to your platform.
  • Schema comprehension: Reads uploaded schema files, SQL dumps, or diagram descriptions to understand tables, columns, keys, and relationships before crafting the query.
  • Optimization guidance: Adds comments, performance tips, and optional test scripts; ideal for reporting, ad-hoc analysis, feature metrics, or translating product questions into data.
  • Use Case: Ask for a reporting query to compare revenue growth across regions while referencing an attached schema, and receive production-ready SQL plus an explanation.

Quick Start

Ask this skill to build a PostgreSQL query that lists active subscribers with their last login and total spend for the previous month.

Frequently Asked Questions about sql-queries

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

FAQPage Schema
How do I generate SQL queries from natural language requests for BigQuery or PostgreSQL?▼

Generating SQL queries from natural language requires understanding your schema and target dialect. This skill translates plain English data questions into executable, dialect-specific SQL code for platforms like BigQuery, PostgreSQL, MySQL, and Snowflake, reading provided schema files to ensure accurate table and column references.

How do I write a query to compare revenue growth across regions using a database schema?▼

Writing queries against a database schema requires mapping your data request to the correct tables and relationships. You provide the schema file or diagram description, and the skill outputs production-ready SQL with optimization tips and comments, tailored to your specific data warehouse platform.

Does this SQL generation tool support dialect-specific syntax for Snowflake and SQL Server?▼

Yes, this SQL generation tool supports dialect-specific syntax for Snowflake, SQL Server, BigQuery, PostgreSQL, and MySQL. It adjusts the generated code to respect the unique syntax and functions of your target warehouse platform.

Can I optimize ad-hoc analysis queries by providing a SQL dump for schema analysis?▼

Yes, you can optimize ad-hoc analysis queries by providing a SQL dump for schema analysis. The skill reads uploaded schema files or SQL dumps to comprehend tables, columns, and keys, then generates optimized SQL queries complete with performance tips and optional test scripts.

What is the best way to translate product metrics questions into executable SQL code?▼

The best way to translate product metrics questions into executable SQL code is using a dialect-aware generation tool that comprehends your schema. This approach turns natural language reporting requests into precise, optimized queries without manual wrestling with dialect syntax or schema details.

Why does my generated SQL query fail when I switch between MySQL and BigQuery?▼

Generated SQL queries often fail between MySQL and BigQuery due to dialect-specific syntax differences. This skill prevents such errors by respecting dialect-specific syntax during generation, ensuring the outputted code matches the exact requirements of your chosen data warehouse platform.

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