Skill UI

This SDK provides programmatic access to Azure AI Content Understanding, enabling the extraction of structured and semantic content from diverse multimodal sources. It supports analyzing documents (PDF, etc.), images, audio, and video files. Users can leverage prebuilt analyzers (like invoice or document search) or create custom analyzers with specific field schemas for advanced RAG and automated workflow implementations.

This SDK provides programmatic access to Azure AI Content Understanding, enabling the extraction of structured and semantic content from diverse multimodal sources. It supports analyzing documents (PDF, etc.), images, audio, and video files. Users can leverage prebuilt analyzers (like invoice or document search) or create custom analyzers with specific field schemas for advanced RAG and automated workflow implementations.

This SDK provides Java developers with access to advanced image analysis features from Azure AI Vision. It allows applications to perform various visual tasks, including OCR text extraction, generating detailed image captions, detecting specific objects with bounding boxes, recognizing content tags, and performing smart cropping. Use it when building applications that require deep visual understanding of images.

A comprehensive workflow for executing advanced, semantic web searches using Exa. This tool moves beyond simple keyword matching, enabling deep context retrieval by understanding the intent behind the query. Key features include RAG context retrieval, content extraction (summaries, highlights, full text), and robust filtering by date range, specific domains, and content categories. Ideal for building knowledge base search features and complex research pipelines.

This skill manages and refines search results obtained from Exa's neural search API. It provides comprehensive control over content extraction scope, allowing users to selectively retrieve metadata, highlights, full text, or structured summaries. Key features include implementing result caching with TTL, deduplicating citations, and crucial token budget management, ensuring the retrieved context fits within LLM context window limits for robust RAG pipelines.

A comprehensive guide containing minimal working examples for all core Exa search operations. It demonstrates basic metadata search, deep content extraction (text, highlights, summary), finding semantically similar pages, and retrieving content for specified URLs. Ideal for developers starting a new Exa integration or learning advanced RAG patterns.

This advanced workflow executes sophisticated web data gathering tasks. It supports three primary functions: LLM-powered structured data extraction using custom JSON schemas or prompts; efficient batch scraping of multiple known URLs; and rapid site mapping to discover all reachable URLs on a domain. Use this when you require reliable, typed data structures rather than raw markdown content.

A comprehensive pipeline for processing, validating, and optimizing scraped web content from Firecrawl. This tool handles markdown cleaning, structured data extraction using Zod validation, content deduplication, and chunking tailored for Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. It ensures crawled data is standardized, clean, and ready for downstream consumption or knowledge base indexing.

This comprehensive guide identifies common anti-patterns and integration mistakes when using Firecrawl for web scraping and content extraction. It serves as a vital code review checklist, helping developers avoid pitfalls such as unbounded crawling, unspecified output formats, or aggressive API polling, ensuring robust and efficient data pipelines.

This comprehensive reference architecture details a multi-stage pipeline for web scraping and content ingestion using Firecrawl. It seamlessly integrates single-page scraping, site-wide crawling, URL mapping, and structured data extraction. The subsequent processing layer handles cleaning, deduplication, and chunking, making this blueprint ideal for designing robust knowledge bases, RAG systems, and complex AI data pipelines.

This skill provides deep web scraping capabilities, allowing users to extract complex content, take screenshots, and parse PDFs from web pages. It handles advanced interactions like clicking and scrolling, making it ideal for detailed data gathering, batch URL processing, and complex web content analysis.

This guide provides a deep dive into migrating existing presentation content (from PowerPoint, Google Slides, Canva, etc.) to the modern, AI-powered format of Gamma. It details a robust, multi-step workflow: content extraction, content cleaning, and batch regeneration using scripting methods. This approach ensures that the core content is preserved while benefiting from Gamma's superior AI formatting capabilities, moving beyond simple file imports and guaranteeing better results than the original source files.