Provides standardized architectural patterns and Pydantic models for building robust API documentation scrapers.
The Scraper Architecture skill offers a comprehensive framework for designing maintainable scrapers that transform messy HTML documentation into structured, high-quality data. It provides a modular project layout, pre-defined Pydantic models for API endpoints, and multi-strategy extraction patterns designed to handle inconsistent web content. By implementing these best practices for fetching, parsing, and formatting, developers can rapidly build scrapers that output data in JSON, Markdown, or OpenAPI formats while ensuring reliability through defensive error handling and validation.
Key Features
01Implementation patterns for robust error handling and HTTP retries
02Multi-format output formatters including JSON, Markdown, and OpenAPI
03Pre-defined Pydantic data models for API endpoints and metadata
04Multi-strategy parsing patterns for resilient HTML data extraction
05Standardized modular project structure for scraper codebases
060 GitHub stars
Use Cases
01Building systematic data collection tools for developer portal content
02Standardizing scraper development across engineering teams using consistent patterns
03Converting legacy HTML API documentation into modern OpenAPI specifications
