openai-agents-sdk-skill

Build OpenAI Agents SDK assistants with function tools and MCP integration.

Updated Dec 31, 2025
One-click install
npx skills add https://github.com/Aqsagull99/hackathon-2-todo-app --skill openai-agents-sdk-skill
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: openai-agents-sdk-skill
Source: https://github.com/Aqsagull99/hackathon-2-todo-app/tree/main/.claude/skills/openai-agents-sdk-skill
Command: npx skills add https://github.com/Aqsagull99/hackathon-2-todo-app --skill openai-agents-sdk-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables developers to build production-ready AI assistants by providing a complete OpenAI Agents SDK pattern with function tools, MCP server integration, and robust context/history management.

Core Features & Use Cases

  • OpenRouter-powered model integration: Seamless model delivery for agents.
  • Function tools with structured outputs: Typed parameters and results via Pydantic models.
  • MCP server integration: Enable external workspace access and tool orchestration.
  • Context management & history: Maintain dialogue history for coherent interactions.
  • Security and error handling: Safe tool invocation and robust error management.

Quick Start

Process a sample user message to create and manage tasks, e.g., process_message(Add a task: Buy groceries) using the Todo Assistant with a user_id.

Frequently Asked Questions about openai-agents-sdk-skill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build AI agents with MCP server integration?

The OpenAI Agents SDK supports creating production-ready AI assistants by integrating MCP servers for external workspace access, utilizing structured function tools, and maintaining dialogue context history for coherent task management.

What is the best way to manage context and history in OpenAI agents?

Managing context and history in OpenAI agents involves using the SDK's built-in context management pattern to maintain dialogue history, enabling coherent interactions and robust task management when processing sequential user messages.

Can I use OpenRouter for model delivery in OpenAI Agents SDK?

Yes, OpenRouter can be used for model delivery in the OpenAI Agents SDK. This integration provides seamless model configuration to run production-ready AI assistants with robust error handling and secure tool invocation.

How do I create structured function tools with Pydantic models for AI assistants?

You create structured function tools for AI assistants by defining typed parameters and results via Pydantic models within the OpenAI Agents SDK, ensuring safe tool invocation and structured outputs for automated task processing.

Do I need Python to run OpenAI Agents SDK with MCP servers?

Yes, Python is required to run the OpenAI Agents SDK with MCP servers. You must configure a Python environment with the OpenAI Agents SDK, OpenRouter, and MCP server support to ensure secure and reliable operation.

Why does my AI agent lose context when managing tasks across multiple turns?

AI agents lose context during task management when dialogue history is not explicitly maintained. This Skill prevents context loss by implementing a robust context management pattern within the OpenAI Agents SDK to track interaction history.