Vercel AI SDK Skill for Openclaw

A comprehensive toolkit for building high-performance, streaming chat interfaces with support for tool execution and multi-step reasoning.

anderskev
v1.0.1
Apr 22, 2026
0
913
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install vercel-ai-sdk

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install vercel-ai-sdk using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Vercel AI SDK Skill?

The Vercel AI SDK is a specialized framework designed to streamline the integration of Large Language Models into web applications. It provides developers with robust React hooks like useChat and server-side utilities such as streamText to create seamless, real-time conversational experiences.

By leveraging Openclaw Skills, developers can master the SDK's parts-based architecture, which allows for complex message structures containing text, files, and reasoning traces. This skill ensures your AI integrations are not only responsive but also capable of sophisticated tool calls and data handling, essential for modern AI-driven applications.

Vercel AI SDK Skill Use Cases

  • Implementing real-time streaming chat interfaces in React applications.
  • Building AI agents that require complex tool calling and client-side execution.
  • Handling multi-modal interactions including file attachments and document analysis.
  • Developing robust error handling and message regeneration workflows for LLM responses.
  • Optimizing UI performance for high-frequency streaming updates using throttling.

How Vercel AI SDK Skill Works

  1. The client initiates a request via the useChat hook, sending messages and optional metadata to a defined API endpoint.
  2. On the server, incoming UI messages are converted using convertToModelMessages and processed by streamText with specified model providers.
  3. The server generates a streaming response using toUIMessageStreamResponse, adhering to the UI message stream contract.
  4. The client receives the stream and updates the status from submitted to streaming, rendering message parts dynamically.
  5. If tools are invoked, the SDK manages the tool state machine from input-streaming to output-available, triggering client-side or server-side execution as defined.

Vercel AI SDK Skill Setup

To integrate this within your project, install the necessary dependencies and set up your chat hook:

npm install @ai-sdk/react ai

Configure your component:

import { useChat } from '@ai-sdk/react';

const { messages, input, handleInputChange, handleSubmit } = useChat({
  api: '/api/chat',
});

Vercel AI SDK Skill Data Schema & Taxonomy

The Vercel AI SDK utilizes a UIMessage structure that prioritizes a parts-based architecture for flexibility.

Attribute Type Description
id string Unique identifier for the message
role string Identity of the sender (system, user, assistant)
parts Array Specialized content parts: text, file, tool, reasoning
metadata unknown Optional custom data attached to the message
status string The lifecycle state: ready, submitted, streaming, error

Vercel AI SDK Skill Advanced Features

  • Multi-turn tool workflows using the sendAutomaticallyWhen configuration for automated resubmission.
  • Experimental UI throttling via experimental_throttle to reduce re-render overhead during high-speed streams.
  • Custom transport layers using DefaultChatTransport for specialized API request preparation.
  • Full type safety for tools and metadata using InferUITools and Zod schema validation.
  • Support for reasoning traces to display the AI's step-by-step thinking process in the UI.

SKILL.md


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