home / skills / different-ai / agent-bank / ai-sdk
This skill enables consistent AI SDK 6 usage with OpenAI models, optimizing selection, structured output, and tool calling across your codebase.
npx playbooks add skill different-ai/agent-bank --skill ai-sdkReview the files below or copy the command above to add this skill to your agents.
---
name: ai-sdk
description: Use AI SDK 6 with OpenAI models - gpt-5.2 for complex tasks, gpt-5-mini for fast actions
license: MIT
compatibility: opencode
metadata:
audience: developers
workflow: ai-integration
---
## What I Do
- Provide correct patterns for AI SDK 6 with OpenAI
- Ensure consistent model usage across the codebase
- Handle text generation, structured output, and tool calling
## Model Selection
| Model | Use Case | Examples |
| ------------ | ----------------------------------- | ----------------------------------------------- |
| `gpt-5.2` | Complex reasoning, multi-step tasks | Email agents, document analysis, KYB assistance |
| `gpt-5-mini` | Fast actions, simple extraction | Invoice field extraction, quick classifications |
**Default to `gpt-5.2`** unless speed is critical and the task is simple.
## Setup Pattern
Always create the OpenAI provider inline - no abstraction layer needed:
```typescript
import { createOpenAI } from '@ai-sdk/openai';
const openai = createOpenAI({ apiKey: process.env.OPENAI_API_KEY || '' });
```
## Core Patterns
### 1. Text Generation
```typescript
import { generateText } from 'ai';
import { createOpenAI } from '@ai-sdk/openai';
const openai = createOpenAI({ apiKey: process.env.OPENAI_API_KEY || '' });
const result = await generateText({
model: openai('gpt-5.2'),
system: 'You are a helpful assistant.',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(result.text);
```
### 2. Structured Output (generateObject)
For extracting structured data with type safety:
```typescript
import { generateObject } from 'ai';
import { createOpenAI } from '@ai-sdk/openai';
import { z } from 'zod';
const openai = createOpenAI({ apiKey: process.env.OPENAI_API_KEY || '' });
const schema = z.object({
name: z.string(),
email: z.string().email(),
amount: z.number(),
});
const result = await generateObject({
model: openai('gpt-5-mini'), // Use mini for simple extraction
schema,
messages: [
{ role: 'user', content: 'Extract: John Doe, [email protected], $500' },
],
});
console.log(result.object); // Typed as { name: string, email: string, amount: number }
```
### 3. Tool Calling with Agentic Loops
For multi-step AI agents:
```typescript
import { generateText, tool, stepCountIs } from 'ai';
import { createOpenAI } from '@ai-sdk/openai';
import { z } from 'zod';
const openai = createOpenAI({ apiKey: process.env.OPENAI_API_KEY || '' });
const result = await generateText({
model: openai('gpt-5.2'), // Use full model for complex tool orchestration
system: 'You are an assistant that can look up information.',
messages: [{ role: 'user', content: 'What is the weather in Tokyo?' }],
tools: {
getWeather: tool({
description: 'Get weather for a city',
inputSchema: z.object({
city: z.string().describe('City name'),
}),
execute: async ({ city }) => {
// Your implementation
return { temperature: 22, condition: 'sunny' };
},
}),
},
stopWhen: stepCountIs(5), // Allow up to 5 tool call steps
});
// Access tool calls made
const toolCalls = result.steps.flatMap(
(step) => step.toolCalls?.map((tc) => tc.toolName) || [],
);
```
### 4. Streaming (for UI)
```typescript
import { streamText } from 'ai';
import { createOpenAI } from '@ai-sdk/openai';
const openai = createOpenAI({ apiKey: process.env.OPENAI_API_KEY || '' });
const result = await streamText({
model: openai('gpt-5.2'),
messages: [{ role: 'user', content: 'Write a poem' }],
});
for await (const chunk of result.textStream) {
process.stdout.write(chunk);
}
```
## Schema Tips for AI SDK 6
When using `generateObject`, schemas must be carefully structured:
```typescript
// GOOD: Use nullable() for optional fields in AI extraction
const schema = z.object({
required: z.string(),
optional: z.string().nullable(), // AI can return null
});
// GOOD: Describe fields for better extraction
const schema = z.object({
amount: z.number().describe('Invoice amount as a positive number'),
currency: z.string().describe('Currency code: USD, EUR, GBP'),
});
// BAD: Don't use optional() - use nullable() instead
const schema = z.object({
field: z.string().optional(), // May cause issues with some models
});
```
## Lazy Loading
For edge runtimes or to reduce bundle size, use dynamic imports:
```typescript
// Lazily import to avoid bundling in edge runtimes if unused
const { createOpenAI } = await import('@ai-sdk/openai');
const { generateObject } = await import('ai');
const openai = createOpenAI({ apiKey: process.env.OPENAI_API_KEY || '' });
```
## Error Handling
```typescript
try {
const result = await generateObject({
model: openai('gpt-5-mini'),
schema,
messages,
});
return result.object;
} catch (error) {
if (error instanceof Error) {
console.error('[AI] Generation failed:', error.message);
}
// Optionally retry with simpler schema or different model
throw error;
}
```
## Existing Usage in Codebase
| File | Model | Purpose |
| ---------------------------------------------------- | ---------- | ------------------------ |
| `src/app/api/ai-email/route.ts` | gpt-5.2 | Email agent with tools |
| `src/server/routers/invoice-router.ts` | gpt-5-mini | Invoice field extraction |
| `src/app/api/kyb-assistant/route.ts` | gpt-5.2 | KYB form assistance |
| `src/app/api/generate-shareholder-registry/route.ts` | gpt-5.2 | Document generation |
| `src/server/routers/funding-source-router.ts` | gpt-5-mini | Quick extraction |
## When to Use This Skill
- Adding new AI-powered features
- Implementing structured data extraction
- Building AI agents with tool calling
- Migrating from older AI SDK versions
- Choosing between gpt-5.2 and gpt-5-mini
This skill documents practical patterns for using AI SDK 6 with OpenAI models in a CLI-first banking agent project. It prescribes when to use gpt-5.2 versus gpt-5-mini, and provides concise examples for text generation, structured extraction, tool calling, streaming, lazy loading, and error handling. Follow these patterns to ensure consistent, type-safe, and performant AI usage across the codebase.
The skill shows inline provider creation with createOpenAI and demonstrates core helpers: generateText for freeform generation, generateObject for typed structured extraction, tool-based agent loops for multi-step workflows, and streamText for UI streaming. It recommends defaulting to gpt-5.2 for complex reasoning and multi-step tasks, and using gpt-5-mini for fast, simple extractions. Examples include schema guidance (use nullable not optional), lazy dynamic imports, and basic retry/error handling patterns.
Which model should I pick by default?
Default to gpt-5.2 for most tasks. Use gpt-5-mini only when latency matters and the task is a simple extraction or classification.
How should I handle optional fields in schemas?
Use nullable() for fields that may be absent or unknown; avoid optional() because it can cause extraction issues.