MCPInstall

ai-sdk-5

Vercel AI SDK 5 patterns. Trigger: When building AI features with AI SDK v5 (chat, streaming, tools/function calling, UIMessage parts), including migration from v4.

Installs
87
Last 24h
—
Trending rank
—
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/prowler-cloud/prowler --skill ai-sdk-5
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads ai-sdk-5 automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Breaking Changes from AI SDK 4

// ❌ AI SDK 4 (OLD)
import { useChat } from "ai";
const { messages, handleSubmit, input, handleInputChange } = useChat({
  api: "/api/chat",
});

// ✅ AI SDK 5 (NEW)
import { useChat } from "@ai-sdk/react";
import { DefaultChatTransport } from "ai";

const { messages, sendMessage } = useChat({
  transport: new DefaultChatTransport({ api: "/api/chat" }),
});

Client Setup

import { useChat } from "@ai-sdk/react";
import { DefaultChatTransport } from "ai";
import { useState } from "react";

export function Chat() {
  const [input, setInput] = useState("");

  const { messages, sendMessage, isLoading, error } = useChat({
    transport: new DefaultChatTransport({ api: "/api/chat" }),
  });

  const handleSubmit = (e: React.FormEvent) => {
    e.preventDefault();
    if (!input.trim()) return;
    sendMessage({ text: input });
    setInput("");
  };

  return (
    <div>
      <div>
        {messages.map((message) => (
          <Message key={message.id} message={message} />
        ))}
      </div>

      <form onSubmit={handleSubmit}>
        <input
          value={input}
          onChange={(e) => setInput(e.target.value)}
          placeholder="Type a message..."
          disabled={isLoading}
        />
        <button type="submit" disabled={isLoading}>
          Send
        </button>
      </form>

      {error && <div>Error: {error.message}</div>}
    </div>
  );
}

UIMessage Structure (v5)

// ❌ Old: message.content was a string
// ✅ New: message.parts is an array

interface UIMessage {
  id: string;
  role: "user" | "assistant" | "system";
  parts: MessagePart[];
}

type MessagePart =
  | { type: "text"; text: string }
  | { type: "image"; image: string }
  | { type: "tool-call"; toolCallId: string; toolName: string; args: unknown }
  | { type: "tool-result"; toolCallId: string; result: unknown };

// Extract text from parts
function getMessageText(message: UIMessage): string {
  return message.parts
    .filter((part): part is { type: "text"; text: string } => part.type === "text")
    .map((part) => part.text)
    .join("");
}

// Render message
function Message({ message }: { message: UIMessage }) {
  return (
    <div className={message.role === "user" ? "user" : "assistant"}>
      {message.parts.map((part, index) => {
        if (part.type === "text") {
          return <p key={index}>{part.text}</p>;
        }
        if (part.type === "image") {
          return <img key={index} src={part.image} alt="" />;
        }
        return null;
      })}
    </div>
  );
}

Server-Side (Route Handler)

// app/api/chat/route.ts
import { openai } from "@ai-sdk/openai";
import { streamText } from "ai";

export async function POST(req: Request) {
  const { messages } = await req.json();

  const result = await streamText({
    model: openai("gpt-4o"),
    messages,
    system: "You are a helpful assistant.",
  });

  return result.toDataStreamResponse();
}

With LangChain

// app/api/chat/route.ts
import { toUIMessageStream } from "@ai-sdk/langchain";
import { ChatOpenAI } from "@langchain/openai";
import { HumanMessage, AIMessage } from "@langchain/core/messages";

export async function POST(req: Request) {
  const { messages } = await req.json();

  const model = new ChatOpenAI({
    modelName: "gpt-4o",
    streaming: true,
  });

  // Convert UI messages to LangChain format
  const langchainMessages = messages.map((m) => {
    const text = m.parts
      .filter((p) => p.type === "text")
      .map((p) => p.text)
      .join("");
    return m.role === "user"
      ? new HumanMessage(text)
      : new AIMessage(text);
  });

  const stream = await model.stream(langchainMessages);

  return toUIMessageStream(stream).toDataStreamResponse();
}

Streaming with Tools

import { openai } from "@ai-sdk/openai";
import { streamText, tool } from "ai";
import { z } from "zod";

const result = await streamText({
  model: openai("gpt-4o"),
  messages,
  tools: {
    getWeather: tool({
      description: "Get weather for a location",
      parameters: z.object({
        location: z.string().describe("City name"),
      }),
      execute: async ({ location }) => {
        // Fetch weather data
        return { temperature: 72, condition: "sunny" };
      },
    }),
  },
});

useCompletion (Text Generation)

import { useCompletion } from "@ai-sdk/react";
import { DefaultCompletionTransport } from "ai";

const { completion, complete, isLoading } = useCompletion({
  transport: new DefaultCompletionTransport({ api: "/api/complete" }),
});

// Trigger completion
await complete("Write a haiku about");

Error Handling

const { error, messages, sendMessage } = useChat({
  transport: new DefaultChatTransport({ api: "/api/chat" }),
  onError: (error) => {
    console.error("Chat error:", error);
    toast.error("Failed to send message");
  },
});

// Display error
{error && (
  <div className="error">
    {error.message}
    <button onClick={() => sendMessage({ text: lastInput })}>
      Retry
    </button>
  </div>
)}

FAQ

What does the ai-sdk-5 skill do?

Vercel AI SDK 5 patterns. Trigger: When building AI features with AI SDK v5 (chat, streaming, tools/function calling, UIMessage parts), including migration from v4.

How do I install ai-sdk-5?

Run npx skills add https://github.com/prowler-cloud/prowler --skill ai-sdk-5 in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/ai-sdk-5/ (personal) or .claude/skills/ai-sdk-5/ (project).

Which AI agents can use ai-sdk-5?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is ai-sdk-5 safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains ai-sdk-5?

It is published by prowler-cloud in prowler-cloud/prowler. It has 87 recorded installs.

More from prowler-cloud/prowler

View all →

zod-4

prowler-cloud/prowler

Zod 4 schema validation patterns. Trigger: When creating or updating Zod v4 schemas for validation/parsing (forms, request payloads, adapters), including v3 - v4 migration patterns.

zustand-5

prowler-cloud/prowler

Zustand 5 state management patterns. Trigger: When implementing client-side state with Zustand (stores, selectors, persist middleware, slices).

911 installs

react-19

prowler-cloud/prowler

React 19 patterns with React Compiler. Trigger: When writing React 19 components/hooks in .tsx (React Compiler rules, hook patterns, refs as props). If using Next.js App Router/Server Actions, also use nextjs-16.

Frontend & Design671 installs

tailwind-4

prowler-cloud/prowler

Tailwind CSS 4 patterns and best practices. Trigger: When styling with Tailwind (className, variants, cn()), especially when dynamic styling or CSS variables are involved (no var() in className).

Frontend & Design612 installs

django-drf

prowler-cloud/prowler

Django REST Framework patterns. Trigger: When implementing generic DRF APIs (ViewSets, serializers, routers, permissions, filtersets). For Prowler API specifics (RLS/RBAC/Providers), also use prowler-api.

Backend & APIs482 installs

typescript

prowler-cloud/prowler

TypeScript strict patterns and best practices. Trigger: When implementing or refactoring TypeScript in .ts/.tsx (types, interfaces, generics, const maps, type guards, removing any, tightening unknown).

Popular ai & agents skills

View category →

google-agents-cli-publish

google/agents-cli

This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).

AI & Agents513.9K installs

google-agents-cli-eval

google/agents-cli

This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).

AI & Agents513.5K installs

skill-creator

anthropics/skills

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

OfficialAI & Agents416.4K installs

codex-pet

prime-skills/runcomfy-agent-skills

Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.

AI & Agents402.1K installs

full-output-enforcement

leonxlnx/taste-skill

Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

AI & Agents401K installs

executing-plans

obra/superpowers

Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available

AI & Agents245.7K installs