article-enrichment

Convert raw article text into structured brain pages with summaries and quotes.

Updated Jun 10, 2026
One-click install
npx skills add https://github.com/starlink-awaken/omostation-gbrain --skill article-enrichment-starlink-awaken
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: article-enrichment
Source: https://github.com/starlink-awaken/omostation-gbrain/tree/main/skills/article-enrichment
Command: npx skills add https://github.com/starlink-awaken/omostation-gbrain --skill article-enrichment-starlink-awaken

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the problem of information clutter by converting raw, unorganized article text into high-quality, actionable knowledge assets that are easy to reference and synthesize.

Core Features & Use Cases

  • Structured Synthesis: Automatically generates executive summaries, key insights, and "why-it-matters" sections from raw text.
  • Verbatim Citation: Ensures high-value content is preserved through accurate, verbatim quote extraction.
  • Cross-Linking: Automatically enforces back-links to related entities, ensuring the article is integrated into the broader knowledge graph.

Quick Start

Instruct the agent to enrich the article located at the specified path by identifying it as a raw dump that requires synthesis.

Frequently Asked Questions about article-enrichment

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

FAQPage Schema
How do I convert raw article text into structured markdown knowledge pages?

To convert raw article text into structured markdown knowledge pages, the skill parses unorganized text dumps and generates executive summaries, key insights, and verbatim quotes. It then formats this content into actionable brain pages with cross-referenced back-links.

How do I automatically generate executive summaries and verbatim quotes from raw article dumps?

You can generate executive summaries and verbatim quotes from raw article dumps by instructing the agent to enrich the article at a specified path. The skill adheres to strict citation conventions to accurately extract and preserve high-value verbatim content alongside synthesized insights.

Does this article enrichment skill require any specific dependencies or components to function?

No specific dependencies or components are required to use this article enrichment skill. It operates on article-type pages within your brain environment, relying entirely on LLM-based parsing to process raw content and enforce back-linking conventions.

What is the best way to integrate raw articles into a knowledge graph with back-links?

The best way to integrate raw articles into a knowledge graph with back-links is through structured synthesis. The skill automatically enforces back-links to related entities during article enrichment, ensuring each processed page connects seamlessly into the broader knowledge management system.

Can I use this synthesis process for any type of page in my knowledge management system?

No, this synthesis process is specifically designed to operate on article-type pages within the brain. It targets raw article text dumps to improve content quality and cross-reference connectivity, rather than processing arbitrary page formats or data types.