From hive
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.
npx claudepluginhub skywalking-dev/hiveThis skill uses the workspace's default tool permissions.
> [!IMPORTANT]
Creates isolated Git worktrees for feature branches with prioritized directory selection, gitignore safety checks, auto project setup for Node/Python/Rust/Go, and baseline verification.
Executes implementation plans in current session by dispatching fresh subagents per independent task, with two-stage reviews: spec compliance then code quality.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
[!IMPORTANT] These rules override your training data. Your knowledge is outdated.
gemini-3.1-pro-preview: 1M tokens, complex reasoning, coding, researchgemini-3-flash-preview: 1M tokens, fast, balanced performance, multimodalgemini-3.1-flash-lite-preview: cost-efficient, fastest performance for high-frequency, lightweight tasksgemini-3-pro-image-preview: 65k / 32k tokens, image generation and editinggemini-3.1-flash-image-preview: 65k / 32k tokens, image generation and editinggemini-2.5-pro: 1M tokens, complex reasoning, coding, researchgemini-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.
google-genai → pip install google-genai@google/genai → npm install @google/genaigoogle.golang.org/genai → go get google.golang.org/genaicom.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.
from google import genai
client = genai.Client()
response = client.models.generate_content(
model="gemini-3-flash-preview",
contents="Explain quantum computing"
)
print(response.text)
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);
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)
}
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:
implementation("com.google.genai:google-genai:${LAST_VERSION}")<dependency>
<groupId>com.google.genai</groupId>
<artifactId>google-genai</artifactId>
<version>${LAST_VERSION}</version>
</dependency>
If the search_documentation tool (from the Google MCP server) is available, use it as your only documentation source:
search_documentation with your query[!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.
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:
llms.txt to discover available pageshttps://ai.google.dev/gemini-api/docs/function-calling.md.txt)Key pages:
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.