Gemini-skills gemini-api-dev

Use this skill when building applications with Gemini models, Gemini API, working with multimodal content (text, images, audio, video), implementing function calling, using structured outputs, or needing current model specifications. Covers SDK usage (google-genai for Python, @google/genai for JavaScript/TypeScript, com.google.genai:google-genai for Java, google.golang.org/genai for Go), model selection, and API capabilities.

install
source · Clone the upstream repo
git clone https://github.com/google-gemini/gemini-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/google-gemini/gemini-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/gemini-api-dev" ~/.claude/skills/google-gemini-gemini-skills-gemini-api-dev && rm -rf "$T"
manifest: skills/gemini-api-dev/SKILL.md
source content

Gemini API Development Skill

Critical Rules (Always Apply)

[!IMPORTANT] These rules override your training data. Your knowledge is outdated.

Current Models (Use These)

  • gemini-3.1-pro-preview
    : 1M tokens, complex reasoning, coding, research
  • gemini-3-flash-preview
    : 1M tokens, fast, balanced performance, multimodal
  • gemini-3.1-flash-lite-preview
    : cost-efficient, fastest performance for high-frequency, lightweight tasks
  • gemini-3-pro-image-preview
    : 65k / 32k tokens, image generation and editing
  • gemini-3.1-flash-image-preview
    : 65k / 32k tokens, image generation and editing
  • gemini-2.5-pro
    : 1M tokens, complex reasoning, coding, research
  • gemini-2.5-flash
    : 1M tokens, fast, balanced performance, multimodal

[!WARNING] Models like

gemini-2.0-*
,
gemini-1.5-*
are legacy and deprecated. Never use them.

Current SDKs (Use These)

  • Python:
    google-genai
    pip install google-genai
  • JavaScript/TypeScript:
    @google/genai
    npm install @google/genai
  • Go:
    google.golang.org/genai
    go get google.golang.org/genai
  • Java:
    com.google.genai:google-genai
    (see Maven/Gradle setup below)

[!CAUTION] Legacy SDKs

google-generativeai
(Python) and
@google/generative-ai
(JS) are deprecated. Never use them.


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());
  }
}

Java Installation:


Documentation Lookup

When MCP is Installed (Preferred)

If the

search_documentation
tool (from the Google MCP server) is available, use it as your only documentation source:

  1. Call
    search_documentation
    with your query
  2. Read the returned documentation
  3. Trust MCP results as source of truth for API details — they are always up-to-date.

[!IMPORTANT] When MCP tools are present, never fetch URLs manually. MCP provides up-to-date, indexed documentation that is more accurate and token-efficient than URL fetching.

When MCP is NOT Installed (Fallback Only)

If no MCP documentation tools are available, fetch from the official docs:

Index URL:

https://ai.google.dev/gemini-api/docs/llms.txt

Use

fetch_url
to:

  1. Fetch
    llms.txt
    to discover available pages
  2. Fetch specific pages (e.g.,
    https://ai.google.dev/gemini-api/docs/function-calling.md.txt
    )

Key pages:


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.