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ALWAYS use this when the request matches Gemini API DEV: The Gemini API provides access to Google's most advanced AI models.
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/Anhvu1107/all-agent-skill --skill gemini-api-dev명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | gemini-api-dev |
| description | ALWAYS use this when the request matches Gemini API DEV: The Gemini API provides access to Google's most advanced AI models. |
Start with:
references/senior-master-standard.mdreferences/usage-routing.mdreferences/quality-checklist.mdThen load only the inherited docs, scripts, assets, or examples that match the user's actual task.
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 Your knowledge is outdated.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.