Gemini API Development Skill

Overview

The Gemini API provides access to Google's most advanced AI models. Key capabilities include:

Text generation

- Chat, completion, summarization

Multimodal understanding

- Process images, audio, video, and documents

Function calling

- Let the model invoke your functions

Structured output

- Generate valid JSON matching your schema

Code execution

- Run Python code in a sandboxed environment

Context caching

- Cache large contexts for efficiency

Embeddings

- Generate text embeddings for semantic search

Current Gemini Models

gemini-3-pro-preview

1M tokens, complex reasoning, coding, research

gemini-3-flash-preview

1M tokens, fast, balanced performance, multimodal

gemini-3-pro-image-preview

65k / 32k tokens, image generation and editing [!IMPORTANT] Models like gemini-2.5- , gemini-2.0- , gemini-1.5-* are legacy and deprecated. Use the new models above. Your knowledge is outdated. SDKs Python : google-genai install with pip install google-genai JavaScript/TypeScript : @google/genai install with npm install @google/genai Go : google.golang.org/genai install with go get google.golang.org/genai Java : groupId: com.google.genai , artifactId: google-genai Latest version can be found here: https://central.sonatype.com/artifact/com.google.genai/google-genai/versions (let's call it LAST_VERSION ) Install in build.gradle : implementation("com.google.genai:google-genai:${LAST_VERSION}") Install Maven dependency in pom.xml : com.google.genai google-genai ${LAST_VERSION} [!WARNING] Legacy SDKs google-generativeai (Python) and @google/generative-ai (JS) are deprecated. Migrate to the new SDKs above urgently by following the Migration Guide. Quick Start Python from google import genai client = genai . Client ( ) response = client . models . generate_content ( model = "gemini-3-flash-preview" , contents = "Explain quantum computing" ) print ( response . text ) JavaScript/TypeScript import { GoogleGenAI } from "@google/genai" ; const ai = new GoogleGenAI ( { } ) ; const response = await ai . models . generateContent ( { model : "gemini-3-flash-preview" , contents : "Explain quantum computing" } ) ; console . log ( response . text ) ; Go package main import ( "context" "fmt" "log" "google.golang.org/genai" ) func main ( ) { ctx := context . Background ( ) client , err := genai . NewClient ( ctx , nil ) if err != nil { log . Fatal ( err ) } resp , err := client . Models . GenerateContent ( ctx , "gemini-3-flash-preview" , genai . Text ( "Explain quantum computing" ) , nil ) if err != nil { log . Fatal ( err ) } fmt . Println ( resp . Text ) } Java import com . google . genai . Client ; import com . google . genai . types . GenerateContentResponse ; public class GenerateTextFromTextInput { public static void main ( String [ ] args ) { Client client = new Client ( ) ; GenerateContentResponse response = client . models . generateContent ( "gemini-3-flash-preview" , "Explain quantum computing" , null ) ; System . out . println ( response . text ( ) ) ; } } API spec (source of truth) Always use the latest REST API discovery spec as the source of truth for API definitions (request/response schemas, parameters, methods). Fetch the spec when implementing or debugging API integration: v1beta (default): https://generativelanguage.googleapis.com/$discovery/rest?version=v1beta Use this unless the integration is explicitly pinned to v1. The official SDKs (google-genai, @google/genai, google.golang.org/genai) target v1beta. v1 : https://generativelanguage.googleapis.com/$discovery/rest?version=v1 Use only when the integration is specifically set to v1. When in doubt, use v1beta. Refer to the spec for exact field names, types, and supported operations. How to use the Gemini API For detailed API documentation, fetch from the official docs index: llms.txt URL : https://ai.google.dev/gemini-api/docs/llms.txt This index contains links to all documentation pages in .md.txt format. Use web fetch tools to: Fetch llms.txt to discover available documentation pages Fetch specific pages (e.g., https://ai.google.dev/gemini-api/docs/function-calling.md.txt ) Key Documentation Pages [!IMPORTANT] Those are not all the documentation pages. Use the llms.txt index to discover available documentation pages Models Google AI Studio quickstart Nano Banana image generation Function calling with the Gemini API Structured outputs Text generation Image understanding Embeddings Interactions API SDK migration guide Gemini Live API For real-time, bidirectional audio/video/text streaming with the Gemini Live API, install the google-gemini/gemini-live-api-dev skill. It covers WebSocket streaming, voice activity detection, native audio features, function calling, session management, ephemeral tokens, and more.