This article explains how to create and manage reusable skills in OpenAI's API. Skills are packaged bundles of files that enable repeatable workflows in hosted or local environments. It covers when to use skills, how to structure them, and the API calls necessary for uploading and utilizing them.

This article outlines how Swagger facilitates API design, testing, and documentation with a focus on AI readiness. It highlights features that enhance collaboration among teams, enforce standards, and streamline workflows for both human and machine consumption. The platform also offers tools for contract testing and exploratory testing to ensure high-quality APIs.

Pulumi Cloud REST API has adopted OpenAPI 3.0, providing a machine-readable specification for the API. This allows for better tooling, client generation, and documentation, ensuring that the API is consistently represented and easier to use. You can access the OpenAPI spec directly via a GET request.

This article argues that traditional documentation for APIs often becomes outdated and unreliable. Instead, it advocates for using type definitions as the definitive contract between services, enabling better integration and fewer errors, especially for AI agents interacting with code.

OpenAI's gpt-oss models utilize the harmony response format to structure conversation outputs, reasoning, and function calls. This format allows for flexible output channels and is designed to integrate seamlessly with existing APIs, while custom implementations can follow the provided guide for proper formatting. Users are encouraged to refer to the documentation for comprehensive instructions on using the format effectively.

Scalar is a minimal and powerful open-source API reference tool that seamlessly integrates with various API frameworks and offers first-class OpenAPI support. It features a user-friendly interface, dynamic parameter handling, and the ability to save requests in organized collections while providing managed hosting options for API documentation. The platform is designed for developers, featuring a modern design and a range of plugins and integrations across multiple programming languages and frameworks.

asyncmcp is an implementation of the MCP protocol that enhances asynchronous communication between clients and servers by utilizing various transport layers like AWS SQS, webhooks, and hybrid methods. It allows for non-blocking requests by directing them to internal queues, facilitating efficient processing without the need for immediate responses. The project offers comprehensive documentation, installation guides, and examples for developers looking to integrate async capabilities into their applications.