Context Engineering Framework

What problem does it solves?

This Skill automates the challenging task of converting diverse unstructured information (websites, documents, text) into structured, AI-interpretable formats. It eliminates manual data preparation, ensuring AI agents have high-quality, organized context for better performance.

Core Features & Use Cases

• Autonomous Context Extraction: Automatically processes various input sources (URLs, raw text, files) to extract and hierarchically structure information.
• Generic Agent Specification: Provides a template for designing autonomous agents capable of information gathering, text analysis, structuring, and persistence.
• Information Source Analysis: Offers templates for manually analyzing and understanding the structure of information sources, especially websites, before automated processing.
• Use Case: You need to train an AI agent on a large set of product documentation spread across multiple web pages and PDF files. Use this Skill to automatically crawl, extract, and structure all relevant information into a consistent YAML format, ready for AI consumption.

Quick Start

Structure the content from the URL 'https://example.com/product-docs' into a YAML format, extracting up to heading level 2.