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llm-query

Extract targeted answers from large text and JSON data with line citations.

Updated Aug 27, 2026
Search Tags:#structured data#data extraction#log analysis#text analysis#large language model
One-click install
npx skills add https://github.com/Balajitechlabs/quickdash-app --skill llm-query-balajitechlabs
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llm-query
Source: https://github.com/Balajitechlabs/quickdash-app/tree/main/.local/skills/llm-query
Command: npx skills add https://github.com/Balajitechlabs/quickdash-app --skill llm-query-balajitechlabs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps users extract concise answers from large text or structured data using an internal Large Language Model (LLM), eliminating the need for manual inspection and providing line citations.

Core Features & Use Cases

  • Query Large Text: Ask focused questions about large text content and receive concise answers with line citations.
  • Structured Data Queries: Query structured JSON data for specific information and receive relevant answers.
  • Use Case: When working with logs or extensive JSON data, quickly find the root cause of an issue or the specific information needed without sifting through large volumes of content.

Quick Start

Run the 'query_with_llm' function with the content and query parameters to get a focused answer from the provided content.

Frequently Asked Questions about llm-query

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

FAQPage Schema
How do I extract specific information from large text or structured JSON data?▼

You can extract specific information from large text or structured JSON data by passing the content and a focused query to an internal LLM. This method analyzes the content and returns concise answers with line citations, eliminating manual inspection.

What is the best way to find the root cause of an issue in large log files?▼

The best way to find the root cause of an issue in large log files is to query the log content using a specialized LLM. It analyzes the extensive textual documents and provides targeted answers, ensuring efficiency and accuracy over manual sifting.

Can I query structured JSON data for specific answers without manual inspection?▼

Yes, you can query structured JSON data for specific answers without manual inspection. By running the query function with your JSON content and targeted question, the internal LLM analyzes the structured data and returns relevant, concise answers.

Does querying large text with an LLM provide citations for the extracted answers?▼

Querying large text with an LLM does provide line citations for the extracted answers. When you ask focused questions about the content, the system ensures you receive concise answers along with citations for easy verification.

What are the limitations of using an LLM for text analysis on extensive documents?▼

The limitations of using an LLM for text analysis on extensive documents are not explicitly defined, but it is specifically designed for scenarios requiring detailed analysis of logs, JSON data, or extensive textual documents to ensure efficiency and accuracy.

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