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allenhutchisonallenhutchison/obsidian-gemini/.agents/skills/gemini-api-dev/SKILL.md

gemini-api-dev

Skill534 starsChanged 36 days agoMITView on GitHub

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.

  • Installs packages

We split this skill into the rules it gives an agent

4 rules. 0 are common, 2 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 12 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

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

    line 133
  2. Very specific:

    Call search_documentation with your query

    line 135
  3. Distinctive:

    Read the returned documentation

    line 136
  4. Distinctive:

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

    line 144

“Common” is measured: kept by at least 6 in 10 of the 12 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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 Your knowledge is outdated.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.

Download now (ZIP)

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  • It worked
  • Partly
  • It didn't
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