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DevOps & Cloud @edwardirby Updated 2/26/2026

Ydc Ai Sdk Integration OpenClaw Skill - ClawHub

Do you want your AI agent to automate Ydc Ai Sdk Integration workflows? This free skill from ClawHub helps with devops & cloud tasks without building custom tools from scratch.

What this skill does

Integrate Vercel AI SDK applications with You.com tools (web search, AI agent, content extraction). Use when developer mentions AI SDK, Vercel AI SDK, generateText, streamText, or You.com integration with AI SDK.

Install

npx clawhub@latest install ydc-ai-sdk-integration

Full SKILL.md

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ydc-ai-sdk-integrationIntegrate Vercel AI SDK applications with You.com tools (web search, AI agent, content extraction). Use when developer mentions AI SDK, Vercel AI SDK, generateText, streamText, or You.com integration with AI SDK.MIT

Integrate AI SDK with You.com Tools

Interactive workflow to add You.com tools to your Vercel AI SDK application using @youdotcom-oss/ai-sdk-plugin.

Workflow

  1. Ask: Package Manager

    • Which package manager? (npm, bun, yarn, pnpm)
    • Install package using their choice:
      npm install @youdotcom-oss/ai-sdk-plugin
      # or bun add @youdotcom-oss/ai-sdk-plugin
      # or yarn add @youdotcom-oss/ai-sdk-plugin
      # or pnpm add @youdotcom-oss/ai-sdk-plugin
      
  2. Ask: Environment Variable Name

    • Using standard YDC_API_KEY?
    • Or custom name? (if custom, get the name)
    • Have they set it in their environment?
    • If NO: Guide them to get key from https://you.com/platform/api-keys
  3. Ask: Which AI SDK Functions?

    • Do they use generateText()?
    • Do they use streamText()?
    • Both?
  4. Ask: Existing Files or New Files?

    • EXISTING: Ask which file(s) to edit
    • NEW: Ask where to create file(s) and what to name them
  5. For Each File, Ask:

    • Which tools to add?
      • youSearch (web search)
      • youExpress (AI agent)
      • youContents (content extraction)
      • Multiple? (which combination?)
    • Using generateText() or streamText() in this file?
    • Which AI provider model? (to determine if stopWhen needed)
  6. Reference Integration Examples

    See "Integration Examples" section below for complete code patterns:

    • generateText() - Basic text generation with tools
    • streamText() - Streaming responses with web frameworks (Next.js, Express, React)
  7. Update/Create Files

    For each file:

    • Reference integration examples (generateText or streamText based on their answer)
    • Add import for selected tools
    • If EXISTING file: Find their generateText/streamText call and add tools object
    • If NEW file: Create file with example structure
    • Tool invocation pattern based on env var name:
      • Standard YDC_API_KEY: youSearch()
      • Custom name: youSearch({ apiKey: process.env.CUSTOM_NAME })
    • Add selected tools to tools object
    • If streamText + Anthropic: Add stopWhen parameter

Integration Examples

generateText() - Basic Text Generation

Environment Variables Setup:

import { anthropic } from '@ai-sdk/anthropic';
import { generateText } from 'ai';
import { youContents, youExpress, youSearch } from '@youdotcom-oss/ai-sdk-plugin';

// Reads YDC_API_KEY from environment automatically
const result = await generateText({
  model: anthropic('claude-sonnet-4-5-20250929'),
  tools: {
    search: youSearch(),
  },
  prompt: 'What are the latest developments in quantum computing?',
});

console.log(result.text);

Multiple Tools:

const result = await generateText({
  model: anthropic('claude-sonnet-4-5-20250929'),
  tools: {
    search: youSearch(),      // Web search with citations
    agent: youExpress(),      // AI answers with web context
    extract: youContents(),   // Content extraction from URLs
  },
  prompt: 'Research quantum computing and summarize the key papers',
});

Custom API Key:

const result = await generateText({
  model: anthropic('claude-sonnet-4-5-20250929'),
  tools: {
    search: youSearch({ apiKey: 'your-custom-key' }),
  },
  prompt: 'Your prompt here',
});

Complete Example:

import { anthropic } from '@ai-sdk/anthropic';
import { generateText } from 'ai';
import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

const main = async () => {
  try {
    const result = await generateText({
      model: anthropic('claude-sonnet-4-5-20250929'),
      tools: {
        search: youSearch(),
      },
      maxSteps: 5,
      prompt: 'What are the latest developments in quantum computing?',
    });

    console.log('Generated text:', result.text);
    console.log('\nTool calls:', result.steps.flatMap(s => s.toolCalls));
  } catch (error) {
    console.error('Error:', error);
    process.exit(1);
  }
};

main();

streamText() - Streaming Responses

Basic Streaming with stopWhen Pattern:

import { anthropic } from '@ai-sdk/anthropic';
import { streamText, type StepResult } from 'ai';
import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

// CRITICAL: Always use stopWhen for Anthropic streaming
// Anthropic's SDK requires explicit stop conditions
const stepCountIs = (n: number) => (stepResult: StepResult<any>) =>
  stepResult.stepNumber >= n;

const result = streamText({
  model: anthropic('claude-sonnet-4-5-20250929'),
  tools: { search: youSearch() },
  stopWhen: stepCountIs(3),  // Required for Anthropic
  prompt: 'What are the latest AI developments?',
});

// Consume stream
for await (const chunk of result.textStream) {
  process.stdout.write(chunk);
}

Next.js Integration (App Router):

// app/api/chat/route.ts
import { anthropic } from '@ai-sdk/anthropic';
import { streamText, type StepResult } from 'ai';
import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

const stepCountIs = (n: number) => (stepResult: StepResult<any>) =>
  stepResult.stepNumber >= n;

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

  const result = streamText({
    model: anthropic('claude-sonnet-4-5-20250929'),
    tools: { search: youSearch() },
    stopWhen: stepCountIs(5),
    prompt,
  });

  return result.toDataStreamResponse();
}

Express.js Integration:

// server.ts
import express from 'express';
import { anthropic } from '@ai-sdk/anthropic';
import { streamText, type StepResult } from 'ai';
import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

const app = express();
app.use(express.json());

const stepCountIs = (n: number) => (stepResult: StepResult<any>) =>
  stepResult.stepNumber >= n;

app.post('/api/chat', async (req, res) => {
  const { prompt } = req.body;

  const result = streamText({
    model: anthropic('claude-sonnet-4-5-20250929'),
    tools: { search: youSearch() },
    stopWhen: stepCountIs(5),
    prompt,
  });

  res.setHeader('Content-Type', 'text/plain; charset=utf-8');
  res.setHeader('Transfer-Encoding', 'chunked');

  for await (const chunk of result.textStream) {
    res.write(chunk);
  }

  res.end();
});

app.listen(3000);

React Client (with Next.js):

// components/Chat.tsx
'use client';

import { useChat } from 'ai/react';

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

  return (
    <div>
      {messages.map(m => (
        <div key={m.id}>
          <strong>{m.role}:</strong> {m.content}
        </div>
      ))}

      <form onSubmit={handleSubmit}>
        <input value={input} onChange={handleInputChange} />
        <button type="submit">Send</button>
      </form>
    </div>
  );
}

Complete Streaming Example:

import { anthropic } from '@ai-sdk/anthropic';
import { streamText, type StepResult } from 'ai';
import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

const stepCountIs = (n: number) => (stepResult: StepResult<any>) =>
  stepResult.stepNumber >= n;

const main = async () => {
  try {
    const result = streamText({
      model: anthropic('claude-sonnet-4-5-20250929'),
      tools: {
        search: youSearch(),
      },
      stopWhen: stepCountIs(3),
      prompt: 'What are the latest AI developments?',
    });

    // Stream to stdout
    console.log('Streaming response:\n');
    for await (const chunk of result.textStream) {
      process.stdout.write(chunk);
    }
    console.log('\n\nDone!');
  } catch (error) {
    console.error('Error:', error);
    process.exit(1);
  }
};

main();

Tool Invocation Patterns

Based on env var name from step 2:

Standard YDC_API_KEY:

import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

tools: {
  search: youSearch(),
}

Custom env var:

import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

const apiKey = process.env.THEIR_CUSTOM_NAME;

tools: {
  search: youSearch({ apiKey }),
}

Multiple tools with standard env var:

import { youSearch, youExpress, youContents } from '@youdotcom-oss/ai-sdk-plugin';

tools: {
  search: youSearch(),
  agent: youExpress(),
  extract: youContents(),
}

Multiple tools with custom env var:

import { youSearch, youExpress, youContents } from '@youdotcom-oss/ai-sdk-plugin';

const apiKey = process.env.THEIR_CUSTOM_NAME;

tools: {
  search: youSearch({ apiKey }),
  agent: youExpress({ apiKey }),
  extract: youContents({ apiKey }),
}

Available Tools

youSearch

Web and news search - model determines parameters (query, count, country, etc.)

youExpress

AI agent with web context - model determines parameters (input, tools)

youContents

Web page content extraction - model determines parameters (urls, format)

Key Integration Patterns

The examples above demonstrate:

  • Import statements (AI SDK + provider + You.com tools)
  • Env var validation (optional for new files)
  • Tool configuration based on env var
  • generateText/streamText usage with tools
  • Result handling (especially textStream destructuring for streamText)
  • Anthropic streaming pattern (stopWhen: stepCountIs(3))
  • Web framework integration (Next.js, Express, React)

Implementation Checklist

For each file being updated/created:

  • [ ] Import added for selected tools
  • [ ] If custom env var: Variable declared with correct name
  • [ ] tools object added to generateText/streamText
  • [ ] Each selected tool invoked correctly:
    • Standard env: toolName()
    • Custom env: toolName({ apiKey })
  • [ ] If streamText: Destructured const { textStream } = ...
  • [ ] If Anthropic + streamText: Added stopWhen: stepCountIs(3)

Global checklist:

  • [ ] Package installed with their package manager
  • [ ] Env var set in their environment
  • [ ] All files updated/created
  • [ ] Ready to test

Common Issues

Issue: "Cannot find module @youdotcom-oss/ai-sdk-plugin" Fix: Install with their package manager

Issue: "YDC_API_KEY (or custom name) environment variable is required" Fix: Set in their environment (get key: https://you.com/platform/api-keys)

Issue: "Tool execution fails with 401" Fix: Verify API key is valid

Issue: "Incomplete or missing response" Fix: If using streamText, increase the step count. Start with 3 and iterate up as needed (see README troubleshooting)

Issue: "textStream is not iterable" Fix: Destructure: const { textStream } = streamText(...)

Issue: "Custom env var not working" Fix: Pass to each tool: youSearch({ apiKey })

Advanced: Tool Development Patterns

For developers creating custom AI SDK tools or contributing to @youdotcom-oss/ai-sdk-plugin:

Tool Function Structure

Each tool function follows this pattern:

export const youToolName = (config: YouToolsConfig = {}) => {
  const apiKey = config.apiKey ?? process.env.YDC_API_KEY;

  return tool({
    description: 'Tool description for AI model',
    inputSchema: ZodSchema,
    execute: async (params) => {
      if (!apiKey) {
        throw new Error('YDC_API_KEY is required');
      }

      const response = await callApiUtility({
        params,
        YDC_API_KEY: apiKey,
        getUserAgent,
      });

      // Return raw API response for maximum flexibility
      return response;
    },
  });
};

Input Schemas Enable Smart Queries

Always use schemas from @youdotcom-oss/mcp:

// ✅ Import from @youdotcom-oss/mcp
import { SearchQuerySchema } from '@youdotcom-oss/mcp';

export const youSearch = (config: YouToolsConfig = {}) => {
  return tool({
    description: '...',
    inputSchema: SearchQuerySchema,  // Enables AI to use all search parameters
    execute: async (params) => { ... },
  });
};

// ❌ Don't duplicate or simplify schemas
const MySearchSchema = z.object({ query: z.string() });  // Missing filters!

Why this matters:

  • Rich schemas enable AI to use advanced query parameters (filters, freshness, country, etc.)
  • AI can construct more intelligent queries based on user intent
  • Prevents duplicating schema definitions across packages
  • Ensures consistency with MCP server schemas

API Key Handling

Always provide environment variable fallback and validate before API calls:

// ✅ Automatic environment variable fallback
const apiKey = config.apiKey ?? process.env.YDC_API_KEY;

// ✅ Check API key in execute function
execute: async (params) => {
  if (!apiKey) {
    throw new Error('YDC_API_KEY is required');
  }
  const response = await callApi(...);
}

Response Format

Always return raw API response for maximum flexibility:

// ✅ Return raw API response
execute: async (params) => {
  const response = await fetchSearchResults({
    searchQuery: params,
    YDC_API_KEY: apiKey,
    getUserAgent,
  });

  return response;  // Raw response for maximum flexibility
}

// ❌ Don't format or transform responses
return {
  text: formatResponse(response),
  data: response,
};

Why raw responses?

  • Maximum flexibility for AI SDK to process results
  • No information loss from formatting
  • AI SDK handles presentation layer
  • Easier to debug (see actual API response)

Tool Descriptions

Write descriptions that guide AI behavior:

// ✅ Clear guidance for AI model
description: 'Search the web for current information, news, articles, and content using You.com. Returns web results with snippets and news articles. Use this when you need up-to-date information or facts from the internet.'

// ❌ Too brief
description: 'Search the web'

Additional Resources

Original URL: https://github.com/openclaw/skills/blob/main/skills/edwardirby/ydc-ai-sdk-integration

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