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shekerkamma
shekerkammaCOMMUNITY
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content-research

Analyze mixed-content URLs and generate structured Obsidian notes with wikilinks.

Updated May 22, 2026
Search Tags:#obsidian#knowledge-graph#web-scraping#content-analysis#second-brain#url-ingestion#content-research
One-click install
npx skills add https://github.com/shekerkamma/peopletech-marketplace --skill content-research-shekerkamma
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: content-research
Source: https://github.com/shekerkamma/peopletech-marketplace/tree/main/plugins/content-tools/skills/content-research
Command: npx skills add https://github.com/shekerkamma/peopletech-marketplace --skill content-research-shekerkamma

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manually collecting, analyzing, and organizing insights from scattered content across YouTube, LinkedIn, GitHub, and web pages is time-consuming and disorganized, making it hard to build a connected, searchable personal or team knowledge base.

Core Features & Use Cases

  • Multi-source content ingestion: Automatically detect and process URLs from video platforms, professional networks, code repositories, and standard web pages in a single command, with no manual source-type configuration needed.
  • Tailored content analysis: Run source-specific analysis including hook and engagement breakdowns for videos and LinkedIn posts, technical and adoption assessments for GitHub repositories, and general content credibility reviews for web pages.
  • Second brain and knowledge graph integration: Auto-save structured notes to your Obsidian vault with wikilinks and backlinks, then feed content into a cross-source knowledge graph to uncover hidden connections between creators, techniques, tools, and concepts.
  • Use Case: Run the skill with a YouTube industry tutorial, a relevant LinkedIn thought leadership post, and a related open-source GitHub repository to get organized, connected insights for a competitive research project in one workflow.

Quick Start

Use the content-research skill by providing one or more URLs of YouTube videos, LinkedIn posts or profiles, GitHub repositories, or web pages to automatically generate structured second-brain notes and add them to your knowledge graph.

Frequently Asked Questions about content-research

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

FAQPage Schema
How do I organize web content from multiple sources into an Obsidian second brain?▼

You can build a second brain by ingesting URLs from video platforms, professional networks, and code repositories to automatically generate structured markdown notes enriched with wikilinks and backlinks.

What is the best way to analyze YouTube videos and GitHub repositories for competitive research?▼

The best way to analyze mixed content for competitive research is running source-specific assessments on URLs, such as engagement breakdowns for videos and technical adoption assessments for repositories, to extract connected insights in one workflow.

Can I build a cross-source knowledge graph from URLs without manual configuration?▼

Yes, you can build a cross-source knowledge graph without manual source-type configuration by processing batches of mixed-content URLs to automatically extract entities and relationships into a queryable structure.

How do I extract entities and relationships from web pages into a queryable knowledge graph?▼

You extract entities and relationships by ingesting standard web pages and other public sources, automatically feeding the discovered creators, techniques, and concepts into a cross-source knowledge graph to uncover hidden connections.

Does this content analysis approach work for both individual URLs and batches of mixed sources?▼

Yes, this content analysis approach works for both individual URLs and batches of mixed sources, automatically detecting source types to eliminate manual organization work across video platforms, professional networks, and standard web pages.

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