
ai-sdk-core
Build backend AI with Vercel AI SDK v5/v6. Covers v6 beta (Agent abstraction, tool approval, reranking), v4→v5 migration (breaking changes), latest models (GPT-5/5.1, Claude 4.x, Gemini 2.5), Workers startup fix, and 12 error solutions (AIAPICallError, AINoObjectGeneratedError, streamText silent errors). Use when: implementing AI SDK v5/v6, migrating v4→v5, troubleshooting errors, fixing Workers startup issues, or updating to latest models.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/ovachiever/droid-tings --skill ai-sdk-core- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads ai-sdk-core automatically when relevant.
- 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.
AI SDK Core
Backend AI with Vercel AI SDK v5 and v6 Beta.
Installation:
npm install ai @ai-sdk/openai @ai-sdk/anthropic @ai-sdk/google zod
# Beta: npm install ai@beta @ai-sdk/openai@beta
AI SDK 6 Beta (November 2025)
Status: Beta (stable release planned end of 2025) Latest: ai@6.0.0-beta.107 (Nov 22, 2025)
New Features
1. Agent Abstraction
Unified interface for building agents with ToolLoopAgent class:
- Full control over execution flow, tool loops, and state management
- Replaces manual tool calling orchestration
2. Tool Execution Approval (Human-in-the-Loop) Request user confirmation before executing tools:
- Static approval: Always ask for specific tools
- Dynamic approval: Conditional based on tool inputs
- Native human-in-the-loop pattern
3. Reranking Support Improve search relevance by reordering documents:
- Supported providers: Cohere, Amazon Bedrock, Together.ai
- Specialized reranking models for RAG workflows
4. Structured Output (Stable) Combine multi-step tool calling with structured data generation:
- Multiple output strategies: objects, arrays, choices, text formats
- Now stable and production-ready in v6
5. Call Options Dynamic runtime configuration:
- Type-safe parameter passing
- RAG integration, model selection, tool customization
- Provider-specific settings adjustments
6. Image Editing (Coming Soon) Native support for image transformation workflows.
Migration from v5
Unlike v4→v5, v6 has minimal breaking changes:
- Powered by v3 Language Model Specification
- Most users require no code changes
- Agent abstraction is additive (opt-in)
Install Beta:
npm install ai@beta @ai-sdk/openai@beta @ai-sdk/react@beta
Official Docs: https://ai-sdk.dev/docs/announcing-ai-sdk-6-beta
Latest AI Models (2025)
OpenAI
GPT-5 (Aug 7, 2025):
- 45% less hallucination than GPT-4o
- State-of-the-art in math, coding, visual perception, health
- Available in ChatGPT, API, GitHub Models, Microsoft Copilot
GPT-5.1 (Nov 13, 2025):
- Improved speed and efficiency over GPT-5
- Available in API platform
import { openai } from '@ai-sdk/openai';
const gpt5 = openai('gpt-5');
const gpt51 = openai('gpt-5.1');
Anthropic
Claude 4 Family (May-Oct 2025):
- Opus 4 (May 22): Best for complex reasoning, $15/$75 per million tokens
- Sonnet 4 (May 22): Balanced performance, $3/$15 per million tokens
- Opus 4.1 (Aug 5): Enhanced agentic tasks, real-world coding
- Sonnet 4.5 (Sept 29): Most capable for coding, agents, computer use
- Haiku 4.5 (Oct 15): Small, fast, low-latency model
import { anthropic } from '@ai-sdk/anthropic';
const sonnet45 = anthropic('claude-sonnet-4-5-20250929'); // Latest
const opus41 = anthropic('claude-opus-4-1-20250805');
const haiku45 = anthropic('claude-haiku-4-5-20251015');
Gemini 2.5 Family (Mar-Sept 2025):
- Pro (March 2025): Most intelligent, #1 on LMArena at launch
- Pro Deep Think (May 2025): Enhanced reasoning mode
- Flash (May 2025): Fast, cost-effective
- Flash-Lite (Sept 2025): Updated efficiency
import { google } from '@ai-sdk/google';
const pro = google('gemini-2.5-pro');
const flash = google('gemini-2.5-flash');
const lite = google('gemini-2.5-flash-lite');
v5 Core Functions (Basics)
generateText() - Text completion with tools streamText() - Real-time streaming generateObject() - Structured output (Zod schemas) streamObject() - Streaming structured data
See official docs for usage: https://ai-sdk.dev/docs/ai-sdk-core
Cloudflare Workers Startup Fix
Problem: AI SDK v5 + Zod causes >270ms startup time (exceeds Workers 400ms limit).
Solution:
// ❌ BAD: Top-level imports cause startup overhead
import { createWorkersAI } from 'workers-ai-provider';
const workersai = createWorkersAI({ binding: env.AI });
// ✅ GOOD: Lazy initialization inside handler
app.post('/chat', async (c) => {
const { createWorkersAI } = await import('workers-ai-provider');
const workersai = createWorkersAI({ binding: c.env.AI });
// ...
});
Additional:
- Minimize top-level Zod schemas
- Move complex schemas into route handlers
- Monitor startup time with Wrangler
v5 Tool Calling Changes
Breaking Changes:
parameters→inputSchema(Zod schema)- Tool properties:
args→input,result→output ToolExecutionErrorremoved (nowtool-errorcontent parts)maxStepsparameter removed → UsestopWhen(stepCountIs(n))
New in v5:
- Dynamic tools (add tools at runtime based on context)
- Agent class (multi-step execution with tools)
Critical v4→v5 Migration
AI SDK v5 introduced extensive breaking changes. If migrating from v4, follow this guide.
Breaking Changes Overview
-
Parameter Renames
maxTokens→maxOutputTokensproviderMetadata→providerOptions
-
Tool Definitions
parameters→inputSchema- Tool properties:
args→input,result→output
-
Message Types
CoreMessage→ModelMessageMessage→UIMessageconvertToCoreMessages→convertToModelMessages
-
Tool Error Handling
ToolExecutionErrorclass removed- Now
tool-errorcontent parts - Enables automated retry
-
Multi-Step Execution
maxSteps→stopWhen- Use
stepCountIs()orhasToolCall()
-
Message Structure
- Simple
contentstring →partsarray - Parts: text, file, reasoning, tool-call, tool-result
- Simple
-
Streaming Architecture
- Single chunk → start/delta/end lifecycle
- Unique IDs for concurrent streams
-
Tool Streaming
- Enabled by default
toolCallStreamingoption removed
-
Package Reorganization
ai/rsc→@ai-sdk/rscai/react→@ai-sdk/reactLangChainAdapter→@ai-sdk/langchain
Migration Examples
Before (v4):
import { generateText } from 'ai';
const result = await generateText({
model: openai.chat('gpt-4'),
maxTokens: 500,
providerMetadata: { openai: { user: 'user-123' } },
tools: {
weather: {
description: 'Get weather',
parameters: z.object({ location: z.string() }),
execute: async (args) => { /* args.location */ },
},
},
maxSteps: 5,
});
After (v5):
import { generateText, tool, stopWhen, stepCountIs } from 'ai';
const result = await generateText({
model: openai('gpt-4'),
maxOutputTokens: 500,
providerOptions: { openai: { user: 'user-123' } },
tools: {
weather: tool({
description: 'Get weather',
inputSchema: z.object({ location: z.string() }),
execute: async ({ location }) => { /* input.location */ },
}),
},
stopWhen: stepCountIs(5),
});
Migration Checklist
- Update all
maxTokenstomaxOutputTokens - Update
providerMetadatatoproviderOptions - Convert tool
parameterstoinputSchema - Update tool execute functions:
args→input - Replace
maxStepswithstopWhen(stepCountIs(n)) - Update message types:
CoreMessage→ModelMessage - Remove
ToolExecutionErrorhandling - Update package imports (
ai/rsc→@ai-sdk/rsc) - Test streaming behavior (architecture changed)
- Update TypeScript types
Automated Migration
AI SDK provides a migration tool:
npx ai migrate
This will update most breaking changes automatically. Review changes carefully.
Official Migration Guide: https://ai-sdk.dev/docs/migration-guides/migration-guide-5-0
Top 12 Errors & Solutions
1. AI_APICallError
Cause: API request failed (network, auth, rate limit).
Solution:
import { AI_APICallError } from 'ai';
try {
const result = await generateText({
model: openai('gpt-4'),
prompt: 'Hello',
});
} catch (error) {
if (error instanceof AI_APICallError) {
console.error('API call failed:', error.message);
console.error('Status code:', error.statusCode);
console.error('Response:', error.responseBody);
// Check common causes
if (error.statusCode === 401) {
// Invalid API key
} else if (error.statusCode === 429) {
// Rate limit - implement backoff
} else if (error.statusCode >= 500) {
// Provider issue - retry
}
}
}
Prevention:
- Validate API keys at startup
- Implement retry logic with exponential backoff
- Monitor rate limits
- Handle network errors gracefully
2. AI_NoObjectGeneratedError
Cause: Model didn't generate valid object matching schema.
Solution:
import { AI_NoObjectGeneratedError } from 'ai';
try {
const result = await generateObject({
model: openai('gpt-4'),
schema: z.object({ /* complex schema */ }),
prompt: 'Generate data',
});
} catch (error) {
if (error instanceof AI_NoObjectGeneratedError) {
console.error('No valid object generated');
// Solutions:
// 1. Simplify schema
// 2. Add more context to prompt
// 3. Provide examples in prompt
// 4. Try different model (gpt-4 better than gpt-3.5 for complex objects)
}
}
Prevention:
- Start with simple schemas, add complexity incrementally
- Include examples in prompt: "Generate a person like: { name: 'Alice', age: 30 }"
- Use GPT-4 for complex structured output
- Test schemas with sample data first
3. Worker Startup Limit (270ms+)
Cause: AI SDK v5 + Zod initialization overhead in Cloudflare Workers exceeds startup limits.
Solution:
// BAD: Top-level imports cause startup overhead
import { createWorkersAI } from 'workers-ai-provider';
import { complexSchema } from './schemas';
const workersai = createWorkersAI({ binding: env.AI });
// GOOD: Lazy initialization inside handler
export default {
async fetch(request, env) {
const { createWorkersAI } = await import('workers-ai-provider');
const workersai = createWorkersAI({ binding: env.AI });
// Use workersai here
}
}
Prevention:
- Move AI SDK imports inside route handlers
- Minimize top-level Zod schemas
- Monitor Worker startup time (must be <400ms)
- Use Wrangler's startup time reporting
GitHub Issue: Search for "Workers startup limit" in Vercel AI SDK issues
4. streamText Fails Silently
Cause: Stream errors can be swallowed by createDataStreamResponse.
Status: ✅ RESOLVED - Fixed in ai@4.1.22 (February 2025)
Solution (Recommended):
// Use the onError callback (added in v4.1.22)
const stream = streamText({
model: openai('gpt-4'),
prompt: 'Hello',
onError({ error }) {
console.error('Stream error:', error);
// Custom error logging and handling
},
});
// Stream safely
for await (const chunk of stream.textStream) {
process.stdout.write(chunk);
}
Alternative (Manual try-catch):
// Fallback if not using onError callback
try {
const stream = streamText({
model: openai('gpt-4'),
prompt: 'Hello',
});
for await (const chunk of stream.textStream) {
process.stdout.write(chunk);
}
} catch (error) {
console.error('Stream error:', error);
}
Prevention:
- Use
onErrorcallback for proper error capture (recommended) - Implement server-side error monitoring
- Test stream error handling explicitly
- Always log on server side in production
GitHub Issue: #4726 (RESOLVED)
5. AI_LoadAPIKeyError
Cause: Missing or invalid API key.
Solution:
import { AI_LoadAPIKeyError } from 'ai';
try {
const result = await generateText({
model: openai('gpt-4'),
prompt: 'Hello',
});
} catch (error) {
if (error instanceof AI_LoadAPIKeyError) {
console.error('API key error:', error.message);
// Check:
// 1. .env file exists and loaded
// 2. Correct env variable name (OPENAI_API_KEY)
// 3. Key format is valid (starts with sk-)
}
}
Prevention:
- Validate API keys at application startup
- Use environment variable validation (e.g., zod)
- Provide clear error messages in development
- Document required environment variables
6. AI_InvalidArgumentError
Cause: Invalid parameters passed to function.
Solution:
import { AI_InvalidArgumentError } from 'ai';
try {
const result = await generateText({
model: openai('gpt-4'),
maxOutputTokens: -1, // Invalid!
prompt: 'Hello',
});
} catch (error) {
if (error instanceof AI_InvalidArgumentError) {
console.error('Invalid argument:', error.message);
// Check parameter types and values
}
}
Prevention:
- Use TypeScript for type checking
- Validate inputs before calling AI SDK functions
- Read function signatures carefully
- Check official docs for parameter constraints
7. AI_NoContentGeneratedError
Cause: Model generated no content (safety filters, etc.).
Solution:
import { AI_NoContentGeneratedError } from 'ai';
try {
const result = await generateText({
model: openai('gpt-4'),
prompt: 'Some prompt',
});
} catch (error) {
if (error instanceof AI_NoContentGeneratedError) {
console.error('No content generated');
// Possible causes:
// 1. Safety filters blocked output
// 2. Prompt triggered content policy
// 3. Model configuration issue
// Handle gracefully:
return { text: 'Unable to generate response. Please try different input.' };
}
}
Prevention:
- Sanitize user inputs
- Avoid prompts that may trigger safety filters
- Have fallback messaging
- Log occurrences for analysis
8. AI_TypeValidationError
Cause: Zod schema validation failed on generated output.
Solution:
import { AI_TypeValidationError } from 'ai';
try {
const result = await generateObject({
model: openai('gpt-4'),
schema: z.object({
age: z.number().min(0).max(120), // Strict validation
}),
prompt: 'Generate person',
});
} catch (error) {
if (error instanceof AI_TypeValidationError) {
console.error('Validation failed:', error.message);
// Solutions:
// 1. Relax schema constraints
// 2. Add more guidance in prompt
// 3. Use .optional() for unreliable fields
}
}
Prevention:
- Start with lenient schemas, tighten gradually
- Use
.optional()for fields that may not always be present - Add validation hints in field descriptions
- Test with various prompts
9. AI_RetryError
Cause: All retry attempts failed.
Solution:
import { AI_RetryError } from 'ai';
try {
const result = await generateText({
model: openai('gpt-4'),
prompt: 'Hello',
maxRetries: 3, // Default is 2
});
} catch (error) {
if (error instanceof AI_RetryError) {
console.error('All retries failed');
console.error('Last error:', error.lastError);
// Check root cause:
// - Persistent network issue
// - Provider outage
// - Invalid configuration
}
}
Prevention:
- Investigate root cause of failures
- Adjust retry configuration if needed
- Implement circuit breaker pattern for provider outages
- Have fallback providers
10. Rate Limiting Errors
Cause: Exceeded provider rate limits (RPM/TPM).
Solution:
// Implement exponential backoff
async function generateWithBackoff(prompt: string, retries = 3) {
for (let i = 0; i < retries; i++) {
try {
return await generateText({
model: openai('gpt-4'),
prompt,
});
} catch (error) {
if (error instanceof AI_APICallError && error.statusCode === 429) {
const delay = Math.pow(2, i) * 1000; // Exponential backoff
console.log(`Rate limited, waiting ${delay}ms`);
await new Promise(resolve => setTimeout(resolve, delay));
} else {
throw error;
}
}
}
throw new Error('Rate limit retries exhausted');
}
Prevention:
- Monitor rate limit headers
- Queue requests to stay under limits
- Upgrade provider tier if needed
- Implement request throttling
11. TypeScript Performance with Zod
Cause: Complex Zod schemas slow down TypeScript type checking.
Solution:
// Instead of deeply nested schemas at top level:
// const complexSchema = z.object({ /* 100+ fields */ });
// Define inside functions or use type assertions:
function generateData() {
const schema = z.object({ /* complex schema */ });
return generateObject({ model: openai('gpt-4'), schema, prompt: '...' });
}
// Or use z.lazy() for recursive schemas:
type Category = { name: string; subcategories?: Category[] };
const CategorySchema: z.ZodType<Category> = z.lazy(() =>
z.object({
name: z.string(),
subcategories: z.array(CategorySchema).optional(),
})
);
Prevention:
- Avoid top-level complex schemas
- Use
z.lazy()for recursive types - Split large schemas into smaller ones
- Use type assertions where appropriate
Official Docs: https://ai-sdk.dev/docs/troubleshooting/common-issues/slow-type-checking
12. Invalid JSON Response (Provider-Specific)
Cause: Some models occasionally return invalid JSON.
Solution:
// Use built-in retry and mode selection
const result = await generateObject({
model: openai('gpt-4'),
schema: mySchema,
prompt: 'Generate data',
mode: 'json', // Force JSON mode (supported by GPT-4)
maxRetries: 3, // Retry on invalid JSON
});
// Or catch and retry manually:
try {
const result = await generateObject({
model: openai('gpt-4'),
schema: mySchema,
prompt: 'Generate data',
});
} catch (error) {
// Retry with different model
const result = await generateObject({
model: openai('gpt-4-turbo'),
schema: mySchema,
prompt: 'Generate data',
});
}
Prevention:
- Use
mode: 'json'when available - Prefer GPT-4 for structured output
- Implement retry logic
- Validate responses
GitHub Issue: #4302 (Imagen 3.0 Invalid JSON)
More Errors: https://ai-sdk.dev/docs/reference/ai-sdk-errors (28 total)
When to Use This Skill
Use ai-sdk-core when:
- Building backend AI features (server-side text generation)
- Implementing server-side text generation (Node.js, Workers, Next.js)
- Creating structured AI outputs (JSON, forms, data extraction)
- Building AI agents with tools (multi-step workflows)
- Integrating multiple AI providers (OpenAI, Anthropic, Google, Cloudflare)
- Migrating from AI SDK v4 to v5
- Encountering AI SDK errors (AI_APICallError, AI_NoObjectGeneratedError, etc.)
- Using AI in Cloudflare Workers (with workers-ai-provider)
- Using AI in Next.js Server Components/Actions
- Need consistent API across different LLM providers
Don't use this skill when:
- Building React chat UIs (use ai-sdk-ui skill instead)
- Need frontend hooks like useChat (use ai-sdk-ui skill instead)
- Need advanced topics like embeddings or image generation (check official docs)
- Building native Cloudflare Workers AI apps without multi-provider (use cloudflare-workers-ai skill instead)
- Need Generative UI / RSC (see https://ai-sdk.dev/docs/ai-sdk-rsc)
Versions
AI SDK:
- Stable: ai@5.0.98 (Nov 20, 2025)
- Beta: ai@6.0.0-beta.107 (Nov 22, 2025)
- Zod 3.x/4.x both supported (3.23.8 recommended)
Latest Models (2025):
- OpenAI: GPT-5.1, GPT-5, o3
- Anthropic: Claude Sonnet 4.5, Opus 4.1, Haiku 4.5
- Google: Gemini 2.5 Pro/Flash/Lite
Check Latest:
npm view ai version
npm view ai dist-tags # See beta versions
Official Docs
Core:
- AI SDK 6 Beta: https://ai-sdk.dev/docs/announcing-ai-sdk-6-beta
- AI SDK Core: https://ai-sdk.dev/docs/ai-sdk-core/overview
- v4→v5 Migration: https://ai-sdk.dev/docs/migration-guides/migration-guide-5-0
- All Errors (28): https://ai-sdk.dev/docs/reference/ai-sdk-errors
- Providers (25+): https://ai-sdk.dev/providers/overview
GitHub:
- Repository: https://github.com/vercel/ai
- Issues: https://github.com/vercel/ai/issues
Last Updated: 2025-11-22 Skill Version: 1.2.0 AI SDK: 5.0.98 stable / 6.0.0-beta.107
FAQ
What does the ai-sdk-core skill do?
Build backend AI with Vercel AI SDK v5/v6. Covers v6 beta (Agent abstraction, tool approval, reranking), v4→v5 migration (breaking changes), latest models (GPT-5/5.1, Claude 4.x, Gemini 2.5), Workers startup fix, and 12 error solutions (AIAPICallError, AINoObjectGeneratedError, streamText silent errors). Use when: implementing AI SDK v5/v6, migrating v4→v5, troubleshooting errors, fixing Workers startup issues, or updating to latest models.
How do I install ai-sdk-core?
Run npx skills add https://github.com/ovachiever/droid-tings --skill ai-sdk-core 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-core/ (personal) or .claude/skills/ai-sdk-core/ (project).
Which AI agents can use ai-sdk-core?
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-core 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-core?
It is published by ovachiever in ovachiever/droid-tings. It has 66 recorded installs.
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