content-core

Extract and normalize text from URLs, PDFs, documents, and media.

167|39|Updated Apr 14, 2025
One-click install
npx skills add https://github.com/lfnovo/content-core --skill content-core
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: content-core
Source: https://github.com/lfnovo/content-core/tree/main
Command: npx skills add https://github.com/lfnovo/content-core --skill content-core

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Content Core removes the hassle of manually copying and cleaning content from websites, documents, and media so you can quickly read, analyze, or summarize what you need.

Core Features & Use Cases

  • Multi-source extraction: Pull readable text from URLs, PDFs, office documents (DOCX/PPTX/XLSX/EPUB), YouTube transcripts, and audio/video files.
  • Summarization with LLMs: Produce concise summaries with optional guidance/context.
  • Engine routing & fallbacks: Automatically selects the best available extraction approach (or lets you force one) and falls back when an engine fails.
  • MCP server integration: Expose extraction and summarization as MCP tools for Claude Desktop and other MCP clients.

Quick Start

Ask the agent: "Extract the text from https://example.com and summarize it in bullet points."

Frequently Asked Questions about content-core

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

FAQPage Schema
How do I extract text from a URL and summarize it?

To extract text from a URL and summarize it, you can use content-core to pull readable text from web pages and pass it to an LLM for concise summarization with optional context. This workflow normalizes web content for deterministic retrieval.

Can I get a YouTube transcript and feed it directly into a summarization workflow?

Yes, YouTube transcript extraction is fully supported. The Skill pulls transcripts directly from YouTube videos and normalizes the text so you can immediately feed the content into an LLM-based summarization workflow.

What is the best way to extract text from PDFs and office documents like DOCX or EPUB?

The best way to extract text from PDFs and office documents is using an engine routing system that automatically selects the optimal extraction method. This approach normalizes DOCX, PPTX, XLSX, and EPUB files into clean text.

Does audio transcription support fallback engines when the primary extraction method fails?

Yes, audio transcription supports engine fallbacks. If the primary extraction engine fails, the system automatically falls back to alternative configured engines to ensure your audio and video files are successfully transcribed.

Can I use this content extraction tool as an MCP server with Claude Desktop?

Yes, you can expose both content extraction and summarization as MCP tools for Claude Desktop and other MCP clients. This integration allows your AI assistant to directly retrieve and normalize text from various sources.

How does web scraping handle content normalization for large or complex pages?

Web scraping handles content normalization by implementing a unified async extraction workflow. This process cleans and normalizes complex web pages into readable text, ensuring the output is ready for LLM-based summarization without manual copying.