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wrenai-query

Convert natural language questions into SQL queries for PostgreSQL and SQL Server databases.

1|Updated Mar 11, 2026
Search Tags:#database#postgresql#data analysis#sql#query#natural language#sql server
One-click install
npx skills add https://github.com/91zgaoge/memoh-X --skill wrenai-query
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: wrenai-query
Source: https://github.com/91zgaoge/memoh-X/tree/main/internal/skills/defaults/wrenai-query
Command: npx skills add https://github.com/91zgaoge/memoh-X --skill wrenai-query

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill allows users to query structured data from PostgreSQL and SQL Server databases using natural language, eliminating the need to write SQL queries manually.

Core Features & Use Cases

  • Natural Language to SQL: Converts user questions into executable SQL queries.
  • Multiple Database Support: Connects to PostgreSQL and SQL Server instances.
  • AI-Powered Analysis: Provides AI-generated analysis of the query results.
  • Use Case: A business analyst needs to know the total sales for the last quarter. Instead of writing a complex SQL query, they can simply ask, "What were the total sales for last quarter?" and receive the answer with an analysis.

Quick Start

Use the wrenai-query skill to ask "查询上个月的KPI指标" against the PostgreSQL database.

Frequently Asked Questions about wrenai-query

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

FAQPage Schema
How do I query a PostgreSQL database using natural language instead of SQL?▼

You can query a PostgreSQL database using natural language by converting your questions into executable SQL queries automatically. This approach eliminates the need to write SQL manually, directly executes the generated query, and returns AI-powered analysis of the retrieved business data.

Can I use natural language to query SQL Server databases for business analytics?▼

Yes, you can use natural language to query SQL Server databases for business analytics. This functionality connects to SQL Server instances, translates your plain English questions into SQL, executes them, and provides an AI-powered analysis of the resulting structured data.

What is the best way to analyze structured data without writing SQL queries manually?▼

The best way to analyze structured data without writing SQL manually is using natural language querying. This mechanism translates your plain questions into executable SQL, fetches the requested data from connected databases, and delivers an AI-generated analysis of the query results instantly.

Does natural language to SQL conversion support querying HR systems and fanwei system data?▼

Yes, natural language to SQL conversion supports querying HR systems and fanwei system data. It connects to multiple database instances simultaneously, allowing you to retrieve and analyze structured information from business data, HR systems, and fanwei system data using plain questions.

How do I get AI-powered analysis for my database query results?▼

To get AI-powered analysis for your database query results, you ask questions in natural language against your PostgreSQL or SQL Server databases. The system automatically generates and runs the SQL query, then provides an AI-generated breakdown and analysis of the retrieved data.

What are the limitations of using natural language to query business data?▼

A limitation of using natural language to query business data is that it currently supports only PostgreSQL and SQL Server databases. Query accuracy depends on how clearly the natural language question is phrased, meaning ambiguous questions may yield incorrect SQL queries or unexpected analysis results.

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