/sql-queries
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
One skill from pm-skills.
shell
$ npx -y skills add phuryn/pm-skills --skill sql-queries --agent claude-codeInstalls just this skill. Get the whole plugin for auto-invocation.
How it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/sql-queries
Context preview
The summary Claude sees to decide when to auto-load this skill.
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
Stats
Stars24,321
Forks2,503
LicenseMIT
SKILL.md
sql-queries.SKILL.md
--- name: sql-queries description: "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." --- # 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
