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query

Translate natural language questions into knowledge graph queries and return graph paths.

2|Updated Mar 22, 2026
Search Tags:#knowledge graph#natural language#AI analysis#data retrieval#graph querying
One-click install
npx skills add https://github.com/jsagir/mindrian-os-plugin --skill query-jsagir
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: query
Source: https://github.com/jsagir/mindrian-os-plugin/tree/main/skills/query
Command: npx skills add https://github.com/jsagir/mindrian-os-plugin --skill query-jsagir

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill enables users to ask questions of the knowledge graph in natural language, simplifying complex data retrieval.

Core Features & Use Cases

  • Natural Language Querying: Ask questions in plain language to retrieve relevant information from the knowledge graph.
  • Graph Path Results: Receive answers as graph paths, facilitating deeper understanding of relationships and connections.
  • Use Case: If you want to find out the connections between two companies in your network, you can ask the Skill, "Show me the connections between Acme Inc. and XYZ Corp."

Quick Start

Ask the Skill, "Who owns company ABC?"

Frequently Asked Questions about query

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

FAQPage Schema
How do I query a knowledge graph using natural language?▼

You can query a knowledge graph using natural language by asking plain language questions, which the system translates into graph queries to retrieve relevant information and return answers as graph paths.

How does natural language processing work for graph data retrieval?▼

Natural language processing for graph data retrieval works by taking your plain language questions and using a graph traversal engine to translate them into structured graph queries, returning connections as graph paths.

Can I find connections between entities in a graph database without writing graph queries?▼

Yes, you can find connections between entities in a graph database without writing graph queries by asking questions in plain natural language. The system translates your input and retrieves the relationship paths automatically.

What is the best way to analyze relationships and connections in a knowledge graph?▼

The best way to analyze relationships in a knowledge graph is using natural language querying. This approach simplifies complex data retrieval by translating your plain language questions directly into graph traversal paths.

Do I need a graph traversal engine to perform natural language querying?▼

Yes, natural language querying requires a graph traversal engine and a natural language processing layer. These components work together to translate your plain language questions into structured graph queries for data retrieval.

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