From antigravity-awesome-skills
Guides developers in using the Gemini API for text generation, multimodal, function calling, structured output, and more. Covers models, SDKs (Python, JS, Go), and API spec.
How this skill is triggered — by the user, by Claude, or both
Slash command
/antigravity-awesome-skills:gemini-api-devThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
The Gemini API provides access to Google's most advanced AI models. Key capabilities include:
The Gemini API provides access to Google's most advanced AI models. Key capabilities include:
gemini-3-pro-preview: 1M tokens, complex reasoning, coding, researchgemini-3-flash-preview: 1M tokens, fast, balanced performance, multimodalgemini-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 Your knowledge is outdated.
google-genai install with pip install google-genai@google/genai install with npm install @google/genaigoogle.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.
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)
}
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:
https://generativelanguage.googleapis.com/$discovery/rest?version=v1betahttps://generativelanguage.googleapis.com/$discovery/rest?version=v1When in doubt, use v1beta. Refer to the spec for exact field names, types, and supported operations.
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:
llms.txt to discover available documentation pageshttps://ai.google.dev/gemini-api/docs/function-calling.md.txt)[!IMPORTANT] Those are not all the documentation pages. Use the
llms.txtindex to discover available documentation pages
This skill is applicable to execute the workflow or actions described in the overview.
npx claudepluginhub sickn33/antigravity-awesome-skills --plugin antigravity-bundle-aas-mobile-app-builderGuides Gemini API development with latest models, capabilities like multimodal processing and function calling, SDKs, and code examples for Python, JavaScript/TypeScript, Go.
Build, integrate, and debug Gemini API applications on Google Cloud Agent Platform using the unified google-genai SDK. Covers text, multimodal, function calling, structured output, embeddings, caching, streaming, Live API, and model tuning across Python, TypeScript, Go, Java, and C#.
Guides @google/genai SDK for Google Gemini API: multimodal generation, function calling, thinking mode, streaming; migrates from deprecated @google/generative-ai, fixes context/format errors.