gemini-api-dev — for Claude Code gemini-api-dev, google-ai-studio-demos, community, for Claude Code, ide skills, gemini-3-pro-preview, gemini-3-flash-preview, gemini-3-pro-image-preview, gemini-2.5-*, gemini-2.0-*

v1.0.0

このスキルについて

適した場面: Ideal for AI agents that need gemini api development skill. ローカライズされた概要: Helper for MLHers running through Google AI Studio demos # Gemini API Development Skill Overview The Gemini API provides access to Google's most advanced AI models. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

機能

Gemini API Development Skill
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

# Core Topics

thisisryanswift thisisryanswift
[0]
[0]
Updated: 4/4/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 10/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
10/11
Quality Score
70
Canonical Locale
en
Detected Body Locale
en

適した場面: Ideal for AI agents that need gemini api development skill. ローカライズされた概要: Helper for MLHers running through Google AI Studio demos # Gemini API Development Skill Overview The Gemini API provides access to Google's most advanced AI models. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

このスキルを使用する理由

推奨ポイント: gemini-api-dev helps agents gemini api development skill. Helper for MLHers running through Google AI Studio demos # Gemini API Development Skill Overview The Gemini API provides access to Google's most

おすすめ

適した場面: Ideal for AI agents that need gemini api development skill.

実現可能なユースケース for gemini-api-dev

ユースケース: Applying Gemini API Development Skill
ユースケース: Applying The Gemini API provides access to Google's most advanced AI models. Key capabilities include:
ユースケース: Applying Text generation - Chat, completion, summarization

! セキュリティと制限

  • 制約事項: Requires repository-specific context from the skill documentation
  • 制約事項: Works best when the underlying tools and dependencies are already configured

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is gemini-api-dev?

適した場面: Ideal for AI agents that need gemini api development skill. ローカライズされた概要: Helper for MLHers running through Google AI Studio demos # Gemini API Development Skill Overview The Gemini API provides access to Google's most advanced AI models. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

How do I install gemini-api-dev?

Run the command: npx killer-skills add thisisryanswift/google-ai-studio-demos. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for gemini-api-dev?

Key use cases include: ユースケース: Applying Gemini API Development Skill, ユースケース: Applying The Gemini API provides access to Google's most advanced AI models. Key capabilities include:, ユースケース: Applying Text generation - Chat, completion, summarization.

Which IDEs are compatible with gemini-api-dev?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for gemini-api-dev?

制約事項: Requires repository-specific context from the skill documentation. 制約事項: Works best when the underlying tools and dependencies are already configured.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add thisisryanswift/google-ai-studio-demos. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use gemini-api-dev immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

gemini-api-dev

Install gemini-api-dev, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

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:
      <dependency>
          <groupId>com.google.genai</groupId>
          <artifactId>google-genai</artifactId>
          <version>${LAST_VERSION}</version>
      </dependency>
      

[!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

python
1from google import genai 2 3client = genai.Client() 4response = client.models.generate_content( 5 model="gemini-3-flash-preview", 6 contents="Explain quantum computing" 7) 8print(response.text)

JavaScript/TypeScript

typescript
1import { GoogleGenAI } from "@google/genai"; 2 3const ai = new GoogleGenAI({}); 4const response = await ai.models.generateContent({ 5 model: "gemini-3-flash-preview", 6 contents: "Explain quantum computing" 7}); 8console.log(response.text);

Go

go
1package main 2 3import ( 4 "context" 5 "fmt" 6 "log" 7 "google.golang.org/genai" 8) 9 10func main() { 11 ctx := context.Background() 12 client, err := genai.NewClient(ctx, nil) 13 if err != nil { 14 log.Fatal(err) 15 } 16 17 resp, err := client.Models.GenerateContent(ctx, "gemini-3-flash-preview", genai.Text("Explain quantum computing"), nil) 18 if err != nil { 19 log.Fatal(err) 20 } 21 22 fmt.Println(resp.Text) 23}

Java

java
1import com.google.genai.Client; 2import com.google.genai.types.GenerateContentResponse; 3 4public class GenerateTextFromTextInput { 5 public static void main(String[] args) { 6 Client client = new Client(); 7 GenerateContentResponse response = 8 client.models.generateContent( 9 "gemini-3-flash-preview", 10 "Explain quantum computing", 11 null); 12 13 System.out.println(response.text()); 14 } 15}

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:

  1. Fetch llms.txt to discover available documentation pages
  2. 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

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.

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