extract

Extract structured knowledge and actionable insights into atomic notes.

20|5|Updated Nov 18, 2025
One-click install
npx skills add https://github.com/zby/llm-do --skill extract-zby
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: extract
Source: https://github.com/zby/llm-do/tree/main/arscontexta/skills/arscontexta-extract
Command: npx skills add https://github.com/zby/llm-do --skill extract-zby

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the extraction of structured knowledge and actionable insights from raw source material, transforming unstructured text into organized, retrievable notes.

Core Features & Use Cases

  • Comprehensive Extraction: Identifies and extracts core claims, patterns, tensions, and implementation ideas from documents.
  • Relevance Filtering: Ensures extracted information directly impacts project development or understanding.
  • Use Case: Feed a research paper or a technical document into this Skill to automatically generate a set of atomic notes detailing key findings, proposed methods, and potential conflicts, ready for integration into your knowledge base.

Quick Start

Use the extract skill to process the content of the provided document.

Frequently Asked Questions about extract

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

FAQPage Schema
How do I extract structured knowledge from unstructured text documents?

This Skill automates the extraction of structured knowledge from unstructured text, identifying core claims and patterns to generate organized, retrievable atomic notes for your knowledge base.

Can I automatically generate atomic notes from a research paper?

Yes, you can generate atomic notes from a research paper by feeding the document into this Skill to automatically extract key findings, proposed methods, and potential conflicts.

How does relevance filtering work for information extraction?

Relevance filtering ensures that extracted information directly impacts project development or understanding, applying a strict filter to general sources while comprehensively processing domain-relevant material.

Do I need a semantic search tool to extract insights from source material?

Yes, this Skill requires a semantic search tool like mcp__qmd__vsearch and file operations to identify, categorize, and store extracted information from source material.

What is the best way to turn technical documents into actionable insights?

Using an extraction Skill that applies relevance filtering to isolate implementation ideas and core claims, storing them as structured atomic notes, is the best way to turn technical documents into actionable insights.

What limitations exist when extracting structured data from general sources?

When extracting structured data from general sources, a relevance limitation applies, filtering information to only include items directly impacting project development rather than comprehensively extracting all available claims.