Is this skill compatible with Next.js?

Absolutely, it features patterns specifically designed for Next.js App Router, including Server Actions and client-side hooks.

How does it handle vector databases?

It includes standardized patterns for generating embeddings and implementing Retrieval-Augmented Generation (RAG) workflows.

Does it support structured data output?

Yes, it includes patterns for using Zod schemas with generateObject to ensure AI responses follow a specific JSON structure.

What LLM providers does this skill support?

It supports major providers including OpenAI, Anthropic (Claude), and Google (Gemini) through the Vercel AI SDK's unified interface.

Can I use this for real-time streaming?

Yes, the skill provides patterns for streaming text responses and tool results using both Route Handlers and Server Actions.

Vercel AI SDK Integrator

Name: Vercel AI SDK Integrator
Author: Naw3

byNaw3

データサイエンスとML

Implements modern AI patterns including streaming responses, tool calling, and structured outputs using the Vercel AI SDK.

概要

This skill provides comprehensive patterns and best practices for building sophisticated AI-powered applications with the Vercel AI SDK. It enables developers to seamlessly integrate multi-provider LLM support, handle streaming data in both server and client environments, and implement advanced features like tool calling, RAG (Retrieval-Augmented Generation), and type-safe structured outputs. Whether building a simple chat interface or a complex agentic system, this skill offers the implementation logic and architectural guidance needed for production-grade AI integration.

主な機能

RAG patterns and embedding generation for vector search
Multi-provider support for OpenAI, Anthropic, and Google Gemini
Type-safe tool calling and function execution implementation
Streaming LLM response patterns for React and Route Handlers
Structured data generation using Zod and generateObject
0 GitHub stars

ユースケース

Developing AI agents that can interact with external APIs through tools
Building real-time AI chat interfaces with streaming responses
Creating data extraction pipelines that output valid JSON schemas

概要

主な機能

RAG patterns and embedding generation for vector search
Multi-provider support for OpenAI, Anthropic, and Google Gemini
Type-safe tool calling and function execution implementation
Streaming LLM response patterns for React and Route Handlers
Structured data generation using Zod and generateObject
0 GitHub stars

ユースケース

Developing AI agents that can interact with external APIs through tools
Building real-time AI chat interfaces with streaming responses
Creating data extraction pipelines that output valid JSON schemas