Skill UI

This skill enables the generation of high-quality images and videos using advanced fal.ai AI models. It is designed for creative professionals, artists, and developers who require powerful, generative visual content. Use this when your task involves transforming text prompts into sophisticated visual media, making it ideal for concept art, multimedia prototyping, or advanced content creation.

Integrates Apple's FoundationModels into iOS apps so developers can run on-device LLMs for text generation, guided structured outputs via @Generable, custom tool calls, and snapshot streaming without leaving the device.

This comprehensive guide provides documentation and code examples for utilizing the Gemini API, Google's advanced multimodal AI platform. It enables developers to power applications with cutting-edge capabilities, including text generation, multimodal understanding (images, audio, video), function calling, and structured data output. Supports major languages like Python, JavaScript, and Go.

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.

This skill provides structured patterns for combining vector similarity search with traditional keyword-based search. It is essential for building advanced Retrieval-Augmented Generation (RAG) systems, sophisticated search engines, or any retrieval task requiring high recall. Use this when pure semantic understanding is insufficient, and precise matching of specific terms (like names or codes) is necessary.

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 skill provides comprehensive methods to significantly reduce expenditure when using the Ideogram API for image generation. Techniques include implementing two-phase generation workflows (drafting with cheap models, finalizing with premium models), batching multiple images in a single API call, caching identical prompts, and setting up robust budget tracking alerts. Ideal for developers managing large-scale creative AI projects.

A comprehensive guide demonstrating how to generate your first AI image using the Ideogram API. It provides runnable examples in cURL, TypeScript, and Python, covering both legacy and V3 endpoints. Users will learn essential API parameters, such as prompt structuring, style types, and aspect ratios, making it ideal for initial integration testing and setup.

A comprehensive reference architecture for implementing large-scale AI image generation using Ideogram. This system guides developers through building robust pipelines, including structured prompt templating (for brand consistency), utilizing multiple API endpoints (Generate, Edit, Remix), and implementing full asset workflow management from generation to final CDN delivery. Ideal for establishing brand asset systems and scalable AI integrations.

This tool allows developers to integrate advanced AI video generation (using Kling AI) directly into continuous integration and continuous deployment pipelines (e.g., GitHub Actions, GitLab CI). Automate the creation of marketing videos, product demos, or regression video testing whenever code changes or a release occurs, ensuring consistent and timely video asset updates.

Implements robust content policy compliance for generative AI prompts and outputs, such as those from Kling AI. This skill provides pre-submission filtering functionality, preventing the generation of restricted content (e.g., violence, explicit material, hate speech) and saving API credits. It includes Python code examples for prompt screening and handling server-side rejection messages.

This skill utilizes the Kling AI API to transform static images into cinematic, animated videos. It supports advanced control mechanisms including motion prompts (describing desired movement), dynamic masks (motion brushing for specific object paths), and static masks (freezing background areas). Users can also define start-to-end frame transitions using `image_tail`. Ideal for content creators needing high-quality, controllable video generation from existing photos.