Build text and voice agents with tools, multi-agent handoffs, guardrails, and human-in-the-loop patterns.
Works with
Supports text agents, realtime voice agents with WebRTC, and multi-agent workflows with automatic delegation via handoffs
Define tools using Zod schemas for type-safe parameter validation; includes structured output support for predictable JSON responses
Implements input/output guardrails for safety validation, human approval workflows for sensitive operations, and streaming supp
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionopenai-agentsExecute the skills CLI command in your project's root directory to begin installation:
Fetches openai-agents from jezweb/claude-skills 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 openai-agents. Access via /openai-agents 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
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Build AI applications with text agents, voice agents (realtime), multi-agent workflows, tools, guardrails, and human-in-the-loop patterns.
npm install @openai/agents zod@4 # v0.4.0+ requires Zod 4 (breaking change)
npm install @openai/agents-realtime # Voice agents
export OPENAI_API_KEY="your-key"
Breaking Change (v0.4.0): Zod 3 no longer supported. Upgrade to zod@4.
Runtimes: Node.js 22+, Deno, Bun, Cloudflare Workers (experimental)
Agents: LLMs with instructions + tools
import { Agent } from '@openai/agents';
const agent = new Agent({ name: 'Assistant', tools: [myTool], model: 'gpt-5-mini' });
Tools: Functions with Zod schemas
import { tool } from '@openai/agents';
import { z } from 'zod';
const weatherTool = tool({
name: 'get_weather',
parameters: z.object({ city: z.string() }),
execute: async ({ city }) => `Weather in ${city}: sunny`,
});
Handoffs: Multi-agent delegation
const triageAgent = Agent.create({ handoffs: [specialist1, specialist2] });
Guardrails: Input/output validation
const agent = new Agent({ inputGuardrails: [detector], outputGuardrails: [filter] });
Structured Outputs: Type-safe responses
const agent = new Agent({ outputType: z.object({ sentiment: z.enum(['positive', 'negative']) }) });
Basic: const result = await run(agent, 'What is 2+2?')
Streaming:
const stream = await run(agent, 'Tell me a story', { stream: true });
for await (const event of stream) {
if (event.type === 'raw_model_stream_event') process.stdout.write(event.data?.choices?.[0]?.delta?.content || '');
}
const billingAgent = new Agent({ name: 'Billing', handoffDescription: 'For billing questions', tools: [refundTool] });
const techAgent = new Agent({ name: 'Technical', handoffDescription: 'For tech issues', tools: [ticketTool] });
const triageAgent = Agent.create({ name: 'Triage', handoffs: [billingAgent, techAgent] });
Agent-as-Tool Context Isolation: When using agent.asTool(), sub-agents do NOT share parent conversation history (intentional design to simplify debugging).
Workaround: Pass context via tool parameters:
const helperTool = tool({
name: 'use_helper',
parameters: z.object({
query: z.string(),
context: z.string().optional(),
}),
execute: async ({ query, context }) => {
return await run(subAgent, `${context}\n\n${query}`);
},
});
Source: Issue #806
Input: Validate before processing
const guardrail: InputGuardrail = {
execute: async ({ input }) => ({ tripwireTriggered: detectHomework(input) })
};
const agent = new Agent({ inputGuardrails: [guardrail] });
Output: Filter responses (PII detection, content safety)
const refundTool = tool({ name: 'process_refund', requiresApproval: true, execute: async ({ amount }) => `Refunded $${amount}` });
let result = await runner.run(input);
while (result.interruption?.type === 'tool_approval') {
result = await promptUser(result.interruption) ? result.state.approve(result.interruption) : result.state.reject(result.interruption);
}
Streaming HITL: When using stream: true with requiresApproval, must explicitly check interruptions:
const stream = await run(agent, input, { stream: true });
let result = await stream.finalResult();
while (result.interruption?.type === 'tool_approval') {
const approved = await promptUser(result.interruption);
result = approved
? await result.state.approve(result.interruption)
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
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
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4.5★★★★★36 reviews- DDiya Desai★★★★★Dec 28, 2024
openai-agents fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- SShikha Mishra★★★★★Dec 16, 2024
Solid pick for teams standardizing on skills: openai-agents is focused, and the summary matches what you get after install.
- DDiya Sanchez★★★★★Dec 16, 2024
I recommend openai-agents for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- EEvelyn Thomas★★★★★Nov 19, 2024
Registry listing for openai-agents matched our evaluation — installs cleanly and behaves as described in the markdown.
- JJames Chen★★★★★Nov 7, 2024
Keeps context tight: openai-agents is the kind of skill you can hand to a new teammate without a long onboarding doc.
- DDiya Park★★★★★Oct 26, 2024
openai-agents is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- VValentina Harris★★★★★Oct 10, 2024
openai-agents reduced setup friction for our internal harness; good balance of opinion and flexibility.
- OOshnikdeep★★★★★Sep 21, 2024
I recommend openai-agents for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- LLuis Khanna★★★★★Sep 21, 2024
openai-agents has been reliable in day-to-day use. Documentation quality is above average for community skills.
- LLiam Thompson★★★★★Sep 17, 2024
openai-agents fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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