develop-ai-functions-example▌
vercel/ai · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Development and validation scripts for AI SDK functions across multiple providers and capabilities.
- ›Organized by AI SDK function category (text generation, streaming, structured output, embeddings, image generation, speech, transcription, reranking, and agents)
- ›File naming convention maps provider and feature combinations (e.g., openai-tool-call.ts , amazon-bedrock-anthropic-cache-control.ts ) for quick identification
- ›Includes shared utility helpers for error handling, environment lo
AI Functions Examples
The examples/ai-functions/ directory contains scripts for validating, testing, and iterating on AI SDK functions across providers.
Example Categories
Examples are organized by AI SDK function in examples/ai-functions/src/:
| Directory | Purpose |
|---|---|
generate-text/ |
Non-streaming text generation with generateText() |
stream-text/ |
Streaming text generation with streamText() |
generate-object/ |
Structured output generation with generateObject() |
stream-object/ |
Streaming structured output with streamObject() |
agent/ |
ToolLoopAgent examples for agentic workflows |
embed/ |
Single embedding generation with embed() |
embed-many/ |
Batch embedding generation with embedMany() |
generate-image/ |
Image generation with generateImage() |
generate-speech/ |
Text-to-speech with generateSpeech() |
transcribe/ |
Audio transcription with transcribe() |
rerank/ |
Document reranking with rerank() |
middleware/ |
Custom middleware implementations |
registry/ |
Provider registry setup and usage |
telemetry/ |
OpenTelemetry integration |
complex/ |
Multi-component examples (agents, routers) |
lib/ |
Shared utilities (not examples) |
tools/ |
Reusable tool definitions |
File Naming Convention
Examples follow the pattern: {provider}-{feature}.ts
| Pattern | Example | Description |
|---|---|---|
{provider}.ts |
openai.ts |
Basic provider usage |
{provider}-{feature}.ts |
openai-tool-call.ts |
Specific feature |
{provider}-{sub-provider}.ts |
amazon-bedrock-anthropic.ts |
Provider with sub-provider |
{provider}-{sub-provider}-{feature}.ts |
google-vertex-anthropic-cache-control.ts |
Sub-provider with feature |
Example Structure
All examples use the run() wrapper from lib/run.ts which:
- Loads environment variables from
.env - Provides error handling with detailed API error logging
Basic Template
import { providerName } from '@ai-sdk/provider-name';
import { generateText } from 'ai';
import { run } from '../lib/run';
run(async () => {
const result = await generateText({
model: providerName('model-id'),
prompt: 'Your prompt here.',
});
console.log(result.text);
console.log('Token usage:', result.usage);
console.log('Finish reason:', result.finishReason);
});
Streaming Template
import { providerName } from '@ai-sdk/provider-name';
import { streamText } from 'ai';
import { printFullStream } from '../lib/print-full-stream';
import { run } from '../lib/run';
run(async () => {
const result = streamText({
model: providerName('model-id'),
prompt: 'Your prompt here.',
});
await printFullStream({ result });
});
Tool Calling Template
import { providerName } from '@ai-sdk/provider-name';
import { generateText, tool } from 'ai';
import { z } from 'zod';
import { run } from '../lib/run';
run(async () => {
const result = await generateText({
model: providerName('model-id'),
tools: {
myTool: tool({
description: 'Tool description',
inputSchema: z.object({
param: z.string().describe('Parameter description'),
}),
execute: async ({ param }) => {
return { result: `Processed: ${param}` };
},
}),
},
prompt: 'Use the tool to...',
});
console.log(JSON.stringify(result, null, 2));
});
Structured Output Template
import { providerName } from '@ai-sdk/provider-name';
import { generateObject } from 'ai';
import { z } from 'zod';
import { run } from '../lib/run';
run(async () => {
const result = await generateObject({
model: providerName('model-id'),
schema: z.object({
name: z.string(),
items: z.array(z.string()),
}),
prompt: 'Generate a...',
});
console.log(JSON.stringify(result.object, null, 2));
console.log('Token usage:', result.usage);
});
Running Examples
From the examples/ai-functions directory:
pnpm tsx src/generate-text/openai.ts
pnpm tsx src/stream-text/openai-tool-call.ts
pnpm tsx src/agent/openai-generate.ts
When to Write Examples
Write examples when:
-
Adding a new provider: Create basic examples for each supported API (
generateText,streamText,generateObject, etc.) -
Implementing a new feature: Demonstrate the feature with at least one provider example
-
Reproducing a bug: Create an example that shows the issue for debugging
-
Adding provider-specific options: Show how to use
providerOptionsfor provider-specific settings -
Creating test fixtures: Use examples to generate API response fixtures (see
capture-api-response-test-fixtureskill)
Utility Helpers
The lib/ directory contains shared utilities:
| File | Purpose |
|---|---|
run.ts |
Error-handling wrapper with .env loading |
print.ts |
Clean object printing (removes undefined values) |
print-full-stream.ts |
Colored streaming output for tool calls, reasoning, text |
save-raw-chunks.ts |
Save streaming chunks for test fixtures |
present-image.ts |
Display images in terminal |
save-audio.ts |
Save audio files to disk |
Using print utilities
import { print } from '../lib/print';
// Pretty print objects without undefined values
print('Result:', result);
printhow to use develop-ai-functions-exampleHow to use develop-ai-functions-example on Cursor
AI-first code editor with Composer
1Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add develop-ai-functions-example
2Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/vercel/ai --skill develop-ai-functions-exampleThe skills CLI fetches develop-ai-functions-example from GitHub repository vercel/ai and configures it for Cursor.
3Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
◆ Which agents do you want to install to?││ ── Universal (.agents/skills) ── always included ────│ • Amp│ • Antigravity│ • Cline│ • Codex│ ●Cursor(selected)│ • Cursor│ • Windsurf4Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/develop-ai-functions-exampleReload or restart Cursor to activate develop-ai-functions-example. Access the skill through slash commands (e.g., /develop-ai-functions-example) or your agent's skill management interface.
⚠Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
Additional Resources
List & Monetize Your Skill
Submit your Claude Code skill and start earning
GET_STARTED →Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
✓Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
✓Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
✓Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
general reviewsRatings
4.5★★★★★52 reviews- ★★★★★Alexander Haddad· Dec 28, 2024
Useful defaults in develop-ai-functions-example — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Camila Farah· Dec 24, 2024
develop-ai-functions-example is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Dhruvi Jain· Dec 16, 2024
develop-ai-functions-example has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Isabella Chawla· Dec 12, 2024
develop-ai-functions-example reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Alexander Nasser· Dec 8, 2024
Solid pick for teams standardizing on skills: develop-ai-functions-example is focused, and the summary matches what you get after install.
- ★★★★★Kofi Li· Dec 8, 2024
Registry listing for develop-ai-functions-example matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Amelia Khanna· Nov 27, 2024
Registry listing for develop-ai-functions-example matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Kaira White· Nov 27, 2024
Solid pick for teams standardizing on skills: develop-ai-functions-example is focused, and the summary matches what you get after install.
- ★★★★★Alexander Lopez· Nov 19, 2024
I recommend develop-ai-functions-example for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Oshnikdeep· Nov 7, 2024
Keeps context tight: develop-ai-functions-example is the kind of skill you can hand to a new teammate without a long onboarding doc.
showing 1-10 of 52
1 / 6