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llm-query

Query large text or JSON with an internal language model and return cited answers.

1|Updated Jul 2, 2026
Search Tags:#text analysis#error diagnosis#language model#line citation#large text analysis
One-click install
npx skills add https://github.com/patriotnewsactivism/ARIA --skill llm-query-patriotnewsactivism
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llm-query
Source: https://github.com/patriotnewsactivism/ARIA/tree/main/.local/skills/llm-query
Command: npx skills add https://github.com/patriotnewsactivism/ARIA --skill llm-query-patriotnewsactivism

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

The llm-query Skill solves the challenge of analyzing large volumes of text or structured content manually, providing a streamlined and accurate method to extract focused answers.

Core Features & Use Cases

  • Focus on Relevant Content: Query an internal LLM directly on specified content, ignoring the rest.
  • Line Citations: Obtain answers with line citations for accurate references.
  • Efficiency: Handle large payloads and avoid the need for logging large payloads into outputs.
  • Use Case: For instance, you have a large log file containing thousands of lines, and you need to find the root cause of a specific error without sifting through each line.

Quick Start

Run the command 'query_with_llm("The error occurred at line 345", "Why did the error happen?")' to get a detailed, precise explanation with citations.

Frequently Asked Questions about llm-query

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

FAQPage Schema
How do I find the root cause of an error in a large log file without reading every line?▼

Large text analysis can be performed by directing an internal language model to focus on specific content and ignore the rest. This method processes complex documents and logs efficiently to return contextually relevant answers with source line citations.

How do I get precise answers from structured JSON without logging large payloads into outputs?▼

You can query structured JSON directly by passing the content and your question to the processing function. It handles large payloads efficiently and returns specific, contextually relevant answers, eliminating the need to log entire payloads into outputs.

Does this large text analysis approach provide citations for the answers it returns?▼

Yes, large text analysis with this approach provides source line citations for accurate references. When you query complex documents or logs, the internal language model returns contextually relevant answers that pinpoint the exact lines containing the information.

What is the best way to analyze complex documents and extract focused answers?▼

The best way to analyze complex documents is to use an internal language model that processes large text or structured JSON for focused queries. It requires minimal input content and returns contextually relevant, specific answers with source line citations.

Can I use a single command to query a specific section of a large text file?▼

Yes, you can use a single command to query specific content by providing the text excerpt and your question. The internal language model analyzes the specified content, ignoring the rest, and returns a detailed, precise explanation with citations.

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