Skill UI

Guides setting up Constitutional AI by combining self-critique SL with RLAIF training to align generative models without human labels and reduce harmful outputs in systems like Claude.

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.

A comprehensive guide to Generative Engine Optimization (GEO), shifting content strategy from traditional SEO (Google ranking) to maximizing citation rates within AI search platforms like ChatGPT, Claude, and Perplexity. Learn how to structure content, build authority, and incorporate schema to be the preferred source for large language models.

This comprehensive guide outlines Apple's Human Interface Guidelines (HIG) for various technologies and user flows (e.g., Siri, Apple Pay, HealthKit, ARKit, Generative AI). It teaches developers how to ensure their applications feel natively integrated, respect user privacy, and adhere to established platform patterns across iOS, macOS, and other Apple devices. Essential reading for building high-quality, compliant, and seamless user experiences.

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 serves as a comprehensive reference guide for Kling AI's various generative models. It details capabilities across video generation (T2V, I2V), image styling, lip sync, and virtual try-on. Users can compare model versions based on quality, speed, and cost to select the optimal model for their creative or production pipeline.

Scaffolds production-ready generative AI agents on Vertex AI with Gemini models, multi-modal tools, RAG, and Cloud Run/Endpoint deployment, including observability and evaluation for enterprise scenarios.

Probabilistic deep-learning framework built on PyTorch for single-cell omics; handles batch correction, integration, multimodal and spatial data, differential expression, and transfer learning with unified APIs.

An expert guide for developing production-grade AI applications, chatbots, and generative UIs using the Vercel AI SDK, Next.js, and React. Covers core concepts including streaming text (`streamText`), managing chat state (`useChat`), implementing complex tool/function calling, and ensuring robust structured data generation (JSON schemas) across multiple LLM providers.

Audit and optimize content for AI search engines and generative AI overviews. Focus on citability, entity clarity, brand signals, and technical accessibility to improve visibility in AI-generated answers and search results. Includes analysis of crawler access and brand mentions.

Performs a full GEO audit of any website by discovering business type, crawling prioritized pages, and delegating parallel subagents to evaluate AI visibility, platform readiness, technical infrastructure, EEAT content, and schema markup, then outputs a composite GEO score with prioritized actions.

Builds AI-powered paid media creative across Meta, Google, TikTok, YouTube, and LinkedIn by combining native platform tools and generative models to automate asset creation, fatigue management, and performance testing while driving ROAS.