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google-ai-docs

Find official Gemini developer documentation on models, guides, and concepts.

7|2|Updated Feb 25, 2026
Search Tags:#gemini#structured output#function calling#context caching#developer guides#multimodal understanding
One-click install
npx skills add https://github.com/wenerme/ai --skill google-ai-docs
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: google-ai-docs
Source: https://github.com/wenerme/ai/tree/main/skills/google-ai-docs
Command: npx skills add https://github.com/wenerme/ai --skill google-ai-docs

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you quickly find and understand the official capabilities, concepts, and developer guidance for Google’s Gemini (Google AI) platform.

Core Features & Use Cases

  • Official Gemini guide coverage: Explains key topics like text generation, reasoning/thinking modes, vision, audio/video understanding, structured output, and tool/function calling.
  • Implementation-ready topics: Includes practical subjects such as code execution, grounding with Google Search, prompt/context caching, and context window management.
  • Compatibility awareness: Covers how Gemini concepts relate to OpenAI SDK compatibility, so you can migrate or design interoperability.

Quick Start

Use the google-ai-docs skill to get the official explanation for how structured output and JSON schema work in Gemini.

Frequently Asked Questions about google-ai-docs

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

FAQPage Schema
How does structured output and JSON schema work in Gemini?▼

Structured output in Gemini uses JSON schema to constrain model responses to specific formats. This feature ensures generated text adheres to defined data structures, enabling reliable parsing for application integration.

What is context caching and how do I use it with the Gemini API?▼

Context caching in the Gemini API stores frequently used large context windows to reduce latency and pricing for repeated requests. It optimizes cost and performance for multimodal understanding tasks.

Can I use the OpenAI SDK with Gemini for function calling?▼

Gemini supports OpenAI SDK compatibility, allowing you to migrate or design interoperability for function calling. This means you can use existing OpenAI tool-augmented generation workflows with Google AI models.

How do I implement code execution and grounding with Google Search in Gemini?▼

Gemini provides official developer guides for implementing code execution and grounding with Google Search. These features allow the model to run code snippets and retrieve real-time web data for accurate responses.

Does Gemini support multimodal understanding for audio and video inputs?▼

Gemini supports multimodal understanding across text, audio, and video inputs. Official documentation explains how to process these diverse formats for comprehensive vision and audio reasoning capabilities.

What are the safety settings and embedding concepts in Google AI developer guides?▼

Google AI developer guides cover safety settings to filter harmful content and embeddings to represent text as vectors. These concepts are essential for building secure and semantically aware applications.

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