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-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondevelop-ai-functions-exampleExecute the skills CLI command in your project's root directory to begin installation:
Fetches develop-ai-functions-example from vercel/ai and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate develop-ai-functions-example. Access via /develop-ai-functions-example in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
0
total installs
0
this week
23.3K
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
23.3K
stars
The examples/ai-functions/ directory contains scripts for validating, testing, and iterating on AI SDK functions across providers.
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 |
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 |
All examples use the run() wrapper from lib/run.ts which:
.envimport { 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);
});
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 });
});
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));
});
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);
});
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
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 providerOptions for provider-specific settings
Creating test fixtures: Use examples to generate API response fixtures (see capture-api-response-test-fixture skill)
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 |
import { print } from '../lib/print';
// Pretty print objects without undefined values
print('Result:', result);
printImplementation 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
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate 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
Related Skills
ml-paper-writing
75davila7/claude-code-templates
AI/MLsame categorybeautiful-mermaid
31intellectronica/agent-skills
AI/MLsame categoryllm-council
26am-will/codex-skills
AI/MLsame categorybrainstorming
16sickn33/antigravity-awesome-skills
AI/MLsame categorydokie-ai-ppt
11myzy-ai/dokie-ai-ppt
AI/MLsame categoryblockchain-developer
10sickn33/antigravity-awesome-skills
AI/MLsame categoryReviews
4.5★★★★★52 reviews- AAlexander 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.
- CCamila Farah★★★★★Dec 24, 2024
develop-ai-functions-example is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- DDhruvi Jain★★★★★Dec 16, 2024
develop-ai-functions-example has been reliable in day-to-day use. Documentation quality is above average for community skills.
- IIsabella Chawla★★★★★Dec 12, 2024
develop-ai-functions-example reduced setup friction for our internal harness; good balance of opinion and flexibility.
- AAlexander 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.
- KKofi Li★★★★★Dec 8, 2024
Registry listing for develop-ai-functions-example matched our evaluation — installs cleanly and behaves as described in the markdown.
- AAmelia Khanna★★★★★Nov 27, 2024
Registry listing for develop-ai-functions-example matched our evaluation — installs cleanly and behaves as described in the markdown.
- KKaira 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.
- AAlexander 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.
- OOshnikdeep★★★★★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 / 6Discussion
Comments — not star reviews- No comments yet — start the thread.