Skill UI

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.

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 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.

This skill automates the complex and tedious process of porting academic papers written in LaTeX from one publisher's journal template (e.g., Springer) to another (e.g., MDPI, IEEE). It executes a structured multi-stage workflow, including content extraction, structural mapping, systematic fixing of common LaTeX issues (like float placement and math environments), and final compilation to ensure the output adheres to the target journal's specifications.

This comprehensive guide provides minimal working examples for key Adobe APIs: Firefly AI image generation, PDF content extraction, and Photoshop background removal. It serves as a practical quickstart for developers starting new Adobe integrations, testing API connectivity, or learning basic API calling patterns using TypeScript and Node.js.

Execute comprehensive document workflows using Adobe PDF Services API. This skill allows you to convert content (HTML/DOCX) into PDFs, extract structured text and tables from existing PDFs using Sensei AI, generate dynamic documents from Word templates, and convert PDFs to Markdown. Ideal for building robust document automation pipelines and advanced content extraction solutions.

A comprehensive tool for interacting with Notion via its API. It allows users to perform workspace-wide searches, run complex queries against structured databases using compound filters (AND/OR), retrieve specific pages, and deeply traverse and extract all nested block content. Supports pagination for handling large datasets, enabling full data visibility and structured data extraction.

A comprehensive skill for handling PowerPoint (.pptx) files. This includes text extraction, deep content analysis via raw XML access (comments, notes, layouts, themes), and programmatic creation of new presentations from scratch. It guides users through design principles, color theory, and structured document generation workflows.

A lightweight utility designed for fetching content from a single URL via HTTP or HTTPS. It supports various methods (GET, POST, PUT, DELETE) and allows configuration of timeouts and maximum response body sizes. This tool is ideal for quick, simple data extraction steps within a workflow DAG, offering significant performance gains over complex LLM agent loops. Note that complex tasks like JS rendering or multi-page crawling require dedicated sub-agents.

This meta-skill automates the complex process of modernizing legacy PDF documents (e.g., historical contracts, scanned manuals, legal documents). It follows a structured four-step pipeline: structural extraction, natural-language rewriting of problem pages, generating an audit summary, and finally re-merging the content into a single, refined PDF. This ensures content is modernized while maintaining fidelity to the original meaning, providing a human review summary before finalization.