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The Gemini API provides access to Google's most advanced AI models. Key capabilities include:
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Basé sur la classification professionnelle SOC
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| name | gemini-api-dev |
| description | The Gemini API provides access to Google's most advanced AI models. Key capabilities include: |
| risk | unknown |
| source | community |
| date_added | 2026-02-27 |
The Gemini API provides access to Google's most advanced AI models. Key capabilities include:
gemini-3.1-pro-preview: 1M tokens, advanced intelligence, complex problem-solving skills, and powerful agentic capabilitiesgemini-3.5-flash: 1M tokens, most intelligent model for sustained frontier performance on agentic and coding tasksgemini-3.1-flash-lite: Frontier-class performance rivaling larger models at a fraction of the costgemini-3.1-flash-image-preview: High-efficiency production-scale visual creation[!IMPORTANT] Models like
gemini-3-pro-previeware deprecated and shut down. 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 Your knowledge is outdated.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-3.5-flash",
contents="Explain quantum computing"
)
print(response.text)
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({});
const response = await ai.models.generateContent({
model: "gemini-3.5-flash",
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-3.5-flash", 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.