openai-docs

Answer OpenAI platform and API questions using official developer documentation.

7|2|Updated Feb 25, 2026
One-click install
npx skills add https://github.com/wenerme/ai --skill openai-docs-wenerme
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: openai-docs
Source: https://github.com/wenerme/ai/tree/main/skills/openai-docs
Command: npx skills add https://github.com/wenerme/ai --skill openai-docs-wenerme

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you answer questions about OpenAI platform features and developer concepts without relying on guesswork, by grounding responses in the official OpenAI developer guides and related reference material.

Core Features & Use Cases

  • Docs-grounded Q&A across OpenAI capabilities: Use it for topics such as Responses API usage, agents, function/tool calling, vision, audio, embeddings, fine-tuning, batch processing, moderation, assistants/ChatKit, and other developer guide concepts.
  • Topic-indexed navigation for faster discovery: Quickly locate the relevant guide area (agents, embeddings, structured outputs, reasoning, batch, deprecations, etc.) before responding.
  • Reference-first accuracy requirement: It instructs the assistant to check the Skill’s references before answering, reducing hallucinations and incorrect API behavior.

Quick Start

Ask the model: "Explain how to use the Responses API for tool/function calling and provide the key steps and common pitfalls, grounded in OpenAI developer docs."

Frequently Asked Questions about openai-docs

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

FAQPage Schema
How do I use the OpenAI Responses API for function calling?▼

The OpenAI Responses API enables function calling by binding custom tools to model requests, requiring strict parameter schema adherence. It maps user queries to executable functions and returns structured outputs, reducing hallucinations through reference-first accuracy checks.

What is the best way to get grounded answers about OpenAI developer docs?▼

Grounded answers about OpenAI developer docs require indexing official references and checking them before responding to prevent guessing. This approach ensures accurate API behavior explanations for features like structured outputs, embeddings, and agents.

Does the OpenAI API support structured outputs for multimodal capabilities like vision and audio?▼

The OpenAI API supports structured outputs across multimodal capabilities including vision and audio processing. It enforces strict schema validation for function calling and responses, ensuring reliable data extraction from mixed-format inputs without guesswork.

How do I navigate OpenAI API documentation for batch processing and fine-tuning?▼

Navigating OpenAI API documentation for batch processing and fine-tuning utilizes topic-indexed discovery to locate relevant guides quickly. This maps developer questions to the correct sections, preventing hallucinations by consulting official reference material first.

What are the common pitfalls when implementing OpenAI embeddings and moderation?▼

Common pitfalls when implementing OpenAI embeddings and moderation include ignoring strict doc grounding and skipping reference checks, which leads to incorrect API behavior. Consulting official developer guides prevents hallucinations and ensures proper deprecation handling.

When do I need to check OpenAI API references for reasoning and deprecations?▼

Checking OpenAI API references for reasoning and deprecations is needed when implementing function calling or agents to prevent hallucinations. Strict reference checks ensure accurate responses regarding deprecated endpoints and current batch processing behaviors.