Skill UI

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.

A comprehensive guide for migrating web scraping pipelines from tools like Puppeteer, Playwright, and Cheerio to Firecrawl. This skill demonstrates how to replace complex, browser-intensive code with simple API calls, handling single-page scraping, structured data extraction using LLMs, and large-scale site crawling, while eliminating the need for manual browser management and anti-bot workarounds.

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.

A comprehensive guide providing reference architectural patterns for building scalable, maintainable, and robust enterprise integrations involving Gamma services. It details three patterns—Basic, Service Layer, and Event-Driven—covering use cases from simple prototypes to high-volume, microservices-based systems, guiding system designers and architects on best practices.

A comprehensive workflow solution for Groq, enabling powerful multimodal tasks beyond simple chat completions. It supports ultra-fast audio transcription (Whisper), detailed image understanding using vision models, and professional text-to-speech generation. Use this for real-time content processing, multimedia analysis, and automated content creation.

A comprehensive guide to optimizing Groq API usage and managing inference costs. Learn techniques such as smart model routing (selecting smaller models for simple tasks), minimizing prompt tokens, batching requests to reduce overhead, and implementing caching for deterministic calls. This guide helps developers achieve significant cost savings and improve system efficiency when handling high-volume AI workloads.

HuggingFace Accelerate adds distributed support to any PyTorch script with just four lines, providing a unified API for DDP, DeepSpeed, FSDP, and Megatron, plus automatic device placement, mixed precision, and simple launch/config commands for fast prototyping.

This skill provides advanced secondary workflows for Ideogram, enabling comprehensive image manipulation beyond simple text-to-image generation. Key functions include Magic Fill (inpainting/editing), Remix (style transfer), Upscaling, describing image content (image-to-text), and re-framing. Ideal for professional image refinement, style transfer, and content enhancement.

This guide provides minimal working examples demonstrating the LangChain Expression Language (LCEL). It shows how to chain together diverse components—such as prompts, LLMs, and output parsers—using simple pipe syntax (e.g., .pipe() or |). Ideal for developers starting a new LangChain project, understanding core AI workflow patterns, or mastering structured data output.

This guide provides a comprehensive strategy for managing and reducing expenses within the Lindy AI platform. Learn how to audit agent credit consumption, right-size models by using less expensive versions for simple tasks, consolidate redundant agents, and optimize trigger frequency. Implementing these steps ensures cost efficiency and sustainable operation of your AI workflows.

This guide demonstrates the basic workflow for building an AI agent using a webhook trigger. The agent receives structured data (payload), utilizes an LLM to extract key information and generate a concise summary (summarization step), and finally executes an action by posting the summary to Slack or sending an email. Ideal for beginners learning about AI agent architecture, testing data flow, and implementing simple automated system notifications.

This skill provides comprehensive reference architectures for integrating Lindy AI agents into production applications. It covers various complex patterns, including simple webhook callbacks, sophisticated event-driven pipelines, multi-agent delegation systems, scheduled workflows, and RAG-powered customer chat interfaces. Essential for designing and building robust, scalable, and reliable AI-powered systems.