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 n...
Best use case
gemini-api-dev is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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 n...
Teams using gemini-api-dev should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/gemini-api-dev/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How gemini-api-dev Compares
| Feature / Agent | gemini-api-dev | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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 n...
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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`
> [!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
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
```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
```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)
}
```
## 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
- [Models](https://ai.google.dev/gemini-api/docs/models.md.txt)
- [Google AI Studio quickstart](https://ai.google.dev/gemini-api/docs/ai-studio-quickstart.md.txt)
- [Nano Banana image generation](https://ai.google.dev/gemini-api/docs/image-generation.md.txt)
- [Function calling with the Gemini API](https://ai.google.dev/gemini-api/docs/function-calling.md.txt)
- [Structured outputs](https://ai.google.dev/gemini-api/docs/structured-output.md.txt)
- [Text generation](https://ai.google.dev/gemini-api/docs/text-generation.md.txt)
- [Image understanding](https://ai.google.dev/gemini-api/docs/image-understanding.md.txt)
- [Embeddings](https://ai.google.dev/gemini-api/docs/embeddings.md.txt)
- [Interactions API](https://ai.google.dev/gemini-api/docs/interactions.md.txt)
- [SDK migration guide](https://ai.google.dev/gemini-api/docs/migrate.md.txt)
## When to Use
This skill is applicable to execute the workflow or actions described in the overview.Related Skills
imagegen-gemini
Generate/edit images via Gemini API (Nano Banana). Triggers: generate image, create picture, AI art, edit image, make illustration.
gemini-image-generator
Generate and edit images using Google Gemini. Use when the user asks to generate, create, edit, or modify images.
gemini-api
Google Gemini API integration for building AI-powered applications. Use when working with Google's Gemini API, Python SDK (google-genai), TypeScript SDK (@google/genai), multimodal inputs (image, video, audio, PDF), thinking/reasoning features, streaming responses, structured outputs with JSON schemas, multi-turn chat, system instructions, image generation (Nano Banana), video generation (Veo), music generation (Lyria), embeddings, document/PDF processing, or any Gemini API integration task. Triggers on mentions of Gemini, Gemini 3, Gemini 2.5, Google AI, Nano Banana, Veo, Lyria, google-genai, or @google/genai SDK usage.
ask-gemini
This skill should be used when the user asks to "ask Gemini", "get Gemini's opinion", "have Gemini review", "improve writing style", "make less AI-sounding", "get feedback on article", "review this draft", or needs a second opinion on content, writing, code, or design. Supports text questions and up to 10 images.
gemini-system-prompt-best-practices
Applies official Google best practices when writing or editing Gemini system prompts (systemInstruction). Use when creating or changing system prompts for Gemini (e.g. transcription, Dictate Prompt, Prompt & Read), when reviewing prompt text in AppConstants or SpeechService, or when the user asks about Gemini prompt design.
gemini-svg-creator
Create professional SVG graphics powered by Gemini 3.1 Pro via the Gemini MCP server. Generates logos, icons, illustrations, infographics, patterns, animated SVGs, and UI elements with a dual-model refinement loop (Claude orchestrates + Gemini generates). Gemini 3.1 Pro has SOTA animated SVG capabilities and advanced reasoning. Use this skill when the user asks to: create an SVG, design a logo, make an icon, draw an illustration, create an infographic, design a pattern, make an animated SVG, generate vector graphics, create SVG art, or any request involving SVG creation or generation. Also triggers on: 'generate SVG', 'draw me', 'design graphic', 'create vector', 'SVG illustration', 'SVG icon', 'SVG animation', 'create badge', 'design emblem', 'make a diagram'.
bgo
Automates the complete Blender build-go workflow, from building and packaging your extension/add-on to removing old versions, installing, enabling, and launching Blender for quick testing and iteration.
mcp-create-declarative-agent
Skill converted from mcp-create-declarative-agent.prompt.md
MCP Architecture Expert
Design and implement Model Context Protocol servers for standardized AI-to-data integration with resources, tools, prompts, and security best practices
mathem-shopping
Automatiserar att logga in på Mathem.se, söka och lägga till varor från en lista eller recept, hantera ersättningar enligt policy och reservera leveranstid, men lämnar varukorgen redo för manuell checkout.
math-modeling
本技能应在用户要求"数学建模"、"建模比赛"、"数模论文"、"数学建模竞赛"、"建模分析"、"建模求解"或提及数学建模相关任务时使用。适用于全国大学生数学建模竞赛(CUMCM)、美国大学生数学建模竞赛(MCM/ICM)等各类数学建模比赛。
matchms
Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.