What is the main benefit of the Responses API over Chat Completions?

The Responses API automatically manages conversation state and preserves model reasoning across turns, which improves multi-turn performance and significantly increases cache utilization.

Does this skill support Model Context Protocol (MCP)?

Yes, it provides specific implementation patterns for connecting OpenAI models to external MCP servers for expanded tool capabilities.

What are polymorphic outputs in this context?

Polymorphic outputs refer to the API's ability to return different types of data (messages, reasoning, function calls, or images) in a single response, all of which are handled by this skill's logic.

How does this skill handle long-running AI tasks?

It utilizes the 'background' mode parameter for tasks exceeding 60 seconds, allowing the application to run asynchronously and poll for completion via the Responses retrieval endpoint.

Can I use this for RAG (Retrieval Augmented Generation)?

Absolutely. It includes templates for the File Search tool, allowing you to upload documents and query them directly within the agentic workflow.

OpenAI Responses API Integration

Name: OpenAI Responses API Integration
Author: secondsky

bysecondsky

•

API開発

Integrates the OpenAI Responses API for stateful agentic applications with reasoning preservation and server-side tool support.

概要

This skill provides a standardized framework for implementing OpenAI's unified Responses API, designed specifically for building production-ready agentic workflows. It enables developers to maintain persistent conversation state and reasoning across multiple turns without manual message history management. With built-in support for server-side tools like Code Interpreter, Web Search, and File Search, as well as native MCP server integration, this skill simplifies the creation of complex AI agents while optimizing cache utilization and performance for the latest models like gpt-5.

主な機能

Preserved reasoning across multi-turn agentic workflows
Built-in server-side tools including Code Interpreter and Web Search
Automatic state management with persistent conversation IDs
Background processing mode for long-running asynchronous tasks
21 GitHub stars
Native Model Context Protocol (MCP) server integration

ユースケース

Migrating legacy Chat Completions implementations to stateful agentic architectures
Developing autonomous agents with real-time web search and code execution capabilities
Building auditable AI systems that require access to model reasoning and polymorphic outputs

概要

主な機能

Preserved reasoning across multi-turn agentic workflows
Built-in server-side tools including Code Interpreter and Web Search
Automatic state management with persistent conversation IDs
Background processing mode for long-running asynchronous tasks
21 GitHub stars
Native Model Context Protocol (MCP) server integration

ユースケース

Migrating legacy Chat Completions implementations to stateful agentic architectures
Developing autonomous agents with real-time web search and code execution capabilities
Building auditable AI systems that require access to model reasoning and polymorphic outputs