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gemini-api-dev
The Gemini API provides access to Google's most advanced AI models. Key capabilities include:
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Installation
Claude Code / Cursor / Codex
$curl -o ~/.claude/skills/gemini-api-dev/SKILL.md --create-dirs "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/plugins/antigravity-awesome-skills-claude/skills/gemini-api-dev/SKILL.md"
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 | multi | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
The Gemini API provides access to Google's most advanced AI models. Key capabilities include:
Which AI agents support this skill?
This skill is compatible with multi.
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 Your knowledge is outdated.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.