gemini-api-dev

# 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 Your knowledge is outdated.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

```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)
}
```

### Java

```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:**

- Latest version: https://central.sonatype.com/artifact/com.google.genai/google-genai/versions
- Gradle: `implementation("com.google.genai:google-genai:${LAST_VERSION}")`
- Maven:
  ```xml
  <dependency>
      <groupId>com.google.genai</groupId>
      <artifactId>google-genai</artifactId>
      <version>${LAST_VERSION}</version>
  </dependency>
  ```

---

## 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:

- [Text generation](https://ai.google.dev/gemini-api/docs/text-generation.md.txt)
- [Function calling](https://ai.google.dev/gemini-api/docs/function-calling.md.txt)
- [Structured outputs](https://ai.google.dev/gemini-api/docs/structured-output.md.txt)
- [Image generation](https://ai.google.dev/gemini-api/docs/image-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)
- [SDK migration guide](https://ai.google.dev/gemini-api/docs/migrate.md.txt)

---

## 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.