openai-api

Build OpenAI API integrations for chat, embeddings, images, audio, and more.

264|11|Updated Apr 25, 2026
One-click install
npx skills add https://github.com/coco-research/coco --skill openai-api-coco-research
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: openai-api
Source: https://github.com/coco-research/coco/tree/main/skills/openai-api
Command: npx skills add https://github.com/coco-research/coco --skill openai-api-coco-research

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openai, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill removes the guesswork from building with OpenAI’s stateless APIs by giving you a complete, production-ready playbook for using the right endpoint, model, and parameters every time.

Core Features & Use Cases

  • Chat Completions: Build GPT-5 and GPT-4o integrations for conversation, reasoning, streaming, and tool use.
  • Embeddings and RAG: Turn text into vectors for semantic search, retrieval, clustering, and knowledge-grounded answers.
  • Images, Audio, and Safety: Generate and edit images, transcribe speech, produce TTS audio, and moderate content with clear thresholds.
  • Use Case: If you are shipping an AI product, this Skill helps you move from a prototype prompt to a robust implementation with examples for streaming, function calling, structured outputs, and edge deployment.

Quick Start

Use the openai-api skill to implement a GPT-5 chat completion with streaming, tool calls, or embeddings by adapting the most relevant example to your input and model choice.

Frequently Asked Questions about openai-api

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

FAQPage Schema
How do I implement OpenAI chat completions with streaming and function calling?

OpenAI chat completions with streaming and function calling are implemented by configuring GPT-5 reasoning parameters and parsing SSE streaming events. This approach supports stateless prompting alongside structured JSON schema validation for tool use responses.

What is the best way to handle OpenAI API rate limits and retries?

Handling OpenAI API rate limits and retries requires implementing exponential backoff logic within your fetch-based or Node.js SDK integration. This ensures production-ready reliability by automatically retrying failed requests without exceeding endpoint thresholds.

How do I build a RAG pipeline using OpenAI embeddings?

Building a RAG pipeline using OpenAI embeddings involves converting text into vectors and managing embedding dimensions correctly. This enables semantic search, clustering, and knowledge-grounded answers by feeding retrieved context into stateless chat completions.

Can I use the OpenAI Node.js SDK for image generation, audio transcription, and moderation?

The OpenAI Node.js SDK supports image generation, audio transcription, and moderation through multipart image and audio handling. Content safety checks are applied with clear thresholds to ensure production-ready outputs.

Does OpenAI GPT-5 support structured outputs and vision capabilities?

GPT-5 supports structured outputs and vision capabilities by utilizing JSON schema validation for deterministic responses and processing image inputs. These features allow for complex multimodal integrations within batch workflows and standard completions.