ai-sdk-handler
Integrate Vercel AI SDK for LLMs, Chatbots, Generative UI, and Agentic Workflows.
Best use case
ai-sdk-handler is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Integrate Vercel AI SDK for LLMs, Chatbots, Generative UI, and Agentic Workflows.
Integrate Vercel AI SDK for LLMs, Chatbots, Generative UI, and Agentic Workflows.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "ai-sdk-handler" skill to help with this workflow task. Context: Integrate Vercel AI SDK for LLMs, Chatbots, Generative UI, and Agentic Workflows.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ai-sdk-handler/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ai-sdk-handler Compares
| Feature / Agent | ai-sdk-handler | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Integrate Vercel AI SDK for LLMs, Chatbots, Generative UI, and Agentic Workflows.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# AI SDK Handler
This skill defines how to implement Large Language Model (LLM) features using the Vercel AI SDK. It covers streaming chat, structured object generation, generative UI, and background agents.
**Note**: For Image/Video generation (Replicate, Fal.ai), continue to use `ai-handler`. Use `ai-sdk-handler` specifically for text, chat, and agentic text/JSON workflows.
## When to Use
- **Chatbots**: Building interactive chat interfaces (`useChat`, `streamText`).
- **Structured Data**: Extracting JSON from text (`generateObject`).
- **Generative UI**: Streaming React components directly from the server (`streamUI`).
- **Agents**: Complex, multi-step reasoning tasks (often combined with Inngest).
- **Multimodal**: Handling image inputs with text.
## Capabilities
### 1. Streaming Chat
- **Tool**: `streamText` (Server), `useChat` (Client).
- **Pattern**: Create a route handler at `src/app/api/chat/route.ts`.
- **Auth**: Wrap with `withAuthRequired` to protect the route.
- **UI**: Use `src/components/chat-ui/` for chat components.
### 2. Generative UI (RSC)
- **Tool**: `streamUI` (Server).
- **Pattern**: Return React components based on tool calls.
- **Use Case**: Dashboards that build themselves, dynamic reports.
### 3. Structured Object Generation
- **Tool**: `generateObject`.
- **Pattern**: Define a Zod schema and get strictly typed JSON back.
- **Use Case**: Populating database forms, extracting itinerary details, categorizing content.
### 4. Background Agents (with Inngest)
- **Tool**: `generateText` / `generateObject` inside Inngest steps.
- **Why**: Next.js Server Actions/Routes have timeouts (max 60s usually). Agents taking longer must run in the background.
- **Pattern**:
1. Trigger Inngest event from UI.
2. Inngest function runs the LLM logic (loops, multi-step).
3. Store result in DB or notify user.
4. **Docs**: [AI SDK Agents](https://ai-sdk.dev/docs/agents/overview).
## Best Practices
1. **Streaming**: Always prefer streaming for text generation > 2 seconds to improve perceived latency.
2. **Auth**: Never expose open AI routes. Always verify `session.user.id`.
3. **Providers**: Use `@ai-sdk/openai` or `@ai-sdk/anthropic`. Abstract the provider configuration in `src/lib/ai/index.ts`.
4. **Backpressure**: The AI SDK handles this automatically in `streamText`.
5. **Caching**: Use `unstable_cache` or KV stores if queries are repetitive.
6. **Prompt Engineering**: Keep prompts in a dedicated folder or constant file if they are complex.
## Documentation & Examples
- **`reference.md`**: Core setup and essential code snippets.
- **`examples.md`**: Exhaustive examples covering:
1. Basic Chat
2. Generative UI
3. Structured Object Generation
4. Agents & Workflows (Loop Control)
5. Caching
6. Streaming Data
7. Reading UI Streams
8. Handling Backpressure
9. Multimodal ChatRelated Skills
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