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sql-queries

Turn everyday questions into SQL queries, the commands used to retrieve and summarize database records. Uses your database structure and platform to produce queries with explanations, performance notes, and optional validation scripts.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Generate SQL queries from natural language descriptions. Supports BigQuery, PostgreSQL, MySQL, and other dialects. Reads database schemas from uploaded diagrams or documentation. Use when writing SQL, building data reports, exploring databases, or translating business questions into queries.

설치 방법 보기

이럴 때 유용합니다

  • Extract users who meet specific activity conditions
  • Build revenue reports by region and customer tier
  • Create queries from database diagrams
  • Understand query logic and validate results

포함된 파일(1)

  • SKILL.md3.5 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

SQL Query Generator

Purpose

Transform natural language requirements into optimized SQL queries across multiple database platforms. This skill helps product managers, analysts, and engineers generate accurate queries without manual syntax work.

How It Works

Step 1: Understand Your Database Schema

  • If you provide a schema file (SQL, documentation, or diagram description), I will read and analyze it
  • Extract table names, column definitions, data types, and relationships
  • Identify primary keys, foreign keys, and indexing strategies

Step 2: Process Your Request

  • Clarify the exact data you need to retrieve or analyze
  • Confirm the SQL dialect (BigQuery, PostgreSQL, MySQL, Snowflake, etc.)
  • Ask for any additional requirements (filters, aggregations, sorting)

Step 3: Generate Optimized Query

  • Write efficient SQL that leverages your database structure
  • Include comments explaining complex logic
  • Add performance considerations for large datasets
  • Provide alternative approaches if applicable

Step 4: Explain and Test

  • Explain the query logic in plain English
  • Suggest how to test or validate results
  • Offer tips for performance optimization
  • If you want, generate a test script or sample data

Usage Examples

Example 1: Query from Schema File

Upload your database_schema.sql file and say:
"Generate a query to find users who signed up in the last 30 days
and had at least 5 active sessions"

Example 2: Query from Diagram Description

"Here's my database: Users table (id, email, created_at), Sessions table
(id, user_id, timestamp, duration). Generate a query for average session
duration per user in January 2026."

Example 3: Complex Analysis Query

"Create a BigQuery query to analyze our revenue by region and customer tier,
including year-over-year growth rates."

Key Capabilities

  • Multi-Dialect Support: Works with BigQuery, PostgreSQL, MySQL, Snowflake, SQL Server
  • File Reading: Reads schema files, SQL dumps, and data documentation
  • Query Optimization: Suggests indexes, partitioning, and performance improvements
  • Explanation: Breaks down queries for learning and documentation
  • Testing: Can generate test queries and sample data scripts
  • Script Execution: Create executable SQL scripts for your database

Tips for Best Results

  1. Provide context: Share your database schema or structure
  2. Be specific: Clearly describe what data you need and any filters
  3. Mention database: Specify which SQL dialect you're using
  4. Include constraints: Mention data volume, time ranges, and performance needs
  5. Request format: Ask for the query result format if you need specific output

Output Format

You'll receive:

  • SQL Query: Production-ready SQL code with comments
  • Explanation: What the query does and how it works
  • Performance Notes: Optimization tips and considerations
  • Test Script (if requested): Sample data and validation queries

Further Reading

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