gemini-api-integration

gemini-api-integration is a skill for Claude Code, Codex from beel-collab/presets.dev. It costs 27 tokens per session (1,448 once invoked), scanned A, a copy of gemini-api-integration, MIT.

Guidance for adding Google Gemini, Google's AI model service, to Node.js, Python, or browser applications.

In plain words
What is it for?
It helps implement text generation, image/audio/video inputs, streamed responses, and function calling, where the model invokes application tools.
Why use it?
It helps resolve setup, model-choice, API errors, rate limits, and quota issues when building Gemini features.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps implement text generation, image/audio/video inputs, streamed responses, and function calling, where the model invokes application tools.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/beel-collab/presets.dev/gemini-api-integration
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add beel-collab/presets.dev --skill gemini-api-integration
Clone the repo
git clone --depth 1 https://github.com/beel-collab/presets.dev

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for gemini-api-integration

README.md
[![agentmods](https://agentmods.dev/badge/skills/beel-collab/presets.dev/gemini-api-integration/github.svg)](https://agentmods.dev/skills/beel-collab/presets.dev/gemini-api-integration)
Your own site
<a href="https://agentmods.dev/skills/beel-collab/presets.dev/gemini-api-integration"><img src="https://agentmods.dev/badge/skills/beel-collab/presets.dev/gemini-api-integration/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for gemini-api-integration

Your own site · 80×15
<a href="https://agentmods.dev/skills/beel-collab/presets.dev/gemini-api-integration"><img src="https://agentmods.dev/badge/skills/beel-collab/presets.dev/gemini-api-integration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,448 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 88% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00027 $0.01448
Opus 5.5 $0.00011 $0.00579
Sonnet 5.5 $0.00005 $0.00290
Haiku 4.5 $0.00003 $0.00145

Measured 1mo ago against content hash 760a0da1283f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

gemini-api-integration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

88% identical to gemini-api-integration — 11 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

claude/skills/automation/gemini-api-integration/SKILL.md · 195 lines

How it starts

The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Gemini API Integration

Overview

This skill guides AI agents through integrating Google Gemini API into applications — from basic text generation to advanced multimodal, function calling, and streaming use cases. It covers the full Gemini SDK lifecycle with production-grade patterns.

When to Use This Skill

  • Use when setting up Gemini API for the first time in a Node.js, Python, or browser project
  • Use when implementing multimodal inputs (text + image/audio/video)
  • Use when adding streaming responses to improve perceived latency
  • Use when implementing function calling / tool use with Gemini
  • Use when optimizing model selection (Flash vs Pro vs Ultra) for cost and performance
  • Use when debugging Gemini API errors, rate limits, or quota issues

Step-by-Step Guide

1. Installation & Setup

Node.js / TypeScript:

npm install @google/generative-ai

Python:

pip install google-generativeai

Set your API key securely:

export GEMINI_API_KEY="your-api-key-here"

2. Basic Text Generation

Node.js:

import { GoogleGenerativeAI } from "@google/generative-ai";

const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);
const model = genAI.getGenerativeModel({ model: "gemini-1.5-flash" });

const result = await model.generateContent("Explain async/await in JavaScript");
console.log(result.response.text());

Python:

import google.generativeai as genai
import os

genai.configure(api_key=os.environ["GEMINI_API_KEY"])
model = genai.GenerativeModel("gemini-1.5-flash")

response = model.generate_content("Explain async/await in JavaScript")
print(response.text)

3. Streaming Responses

const result = await model.generateContentStream("Write a detailed blog post about AI");

for await (const chunk of result.stream) {
  process.stdout.write(chunk.text());
}

4. Multimodal Input (Text + Image)

import fs from "fs";

const imageData = fs.readFileSync("screenshot.png");
const imagePart = {
  inlineData: {
    data: imageData.toString("base64"),
    mimeType: "image/png",
  },
};

const result = await model.generateContent(["Describe this image:", imagePart]);
console.log(result.response.text());

Read the full file on GitHub · 195 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 195 lines · 27 tokens per session scan A 760a0da1283f

Subscribe to this mod's changes

gemini-api-integration is a skill published in the GitHub repository beel-collab/presets.dev (3 stars, last pushed 5mo ago), licensed MIT. It adds 27 tokens to every session and 1,448 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to gemini-api-integration, differing in 11 lines, and is treated as a copy.

Related

Other skills, from other repositories

deepeval

Use when discussing or working with DeepEval (the python AI evaluation framework).

sammcj/agentic-coding · 19 tokens

prompt-enhancer

Transform poor or overly simple prompts with expert-level framing. Use when the user explicitly asks to improve, refine, or rewrite a prompt, or wants help framing a request for another AI system. Do NOT use for authoring, reviewing, or migrating system prompts or skills targeting a specific Claude model.

sammcj/agentic-coding · 63 tokens

ml-llm-wiki

Use when answering questions from this machine-learning knowledge base. Triggers: questions about transformers, attention cost and efficiency, and long-context scaling; 'what do we know about attention', 'check the ML wiki'. Read-only querying of compiled knowledge; to add, update, supersede, lint, audit, or critique…

sammcj/agentic-coding · 80 tokens

llm-prompting-guide

Prompt format rules for generative video and music models. Use when writing or reviewing a prompt for MiniMax H3 (text/image/reference-to-video with native audio) or MiniMax Music 3 (song generation from caption plus lyrics), in ComfyUI or elsewhere. Do NOT use for chat-assistant prompts, or for generative models not…

sammcj/agentic-coding · 79 tokens

azure-search-documents-ts

Build search applications using Azure AI Search SDK for JavaScript (@azure/search-documents). Use when creating/managing indexes, implementing vector/hybrid search, semantic ranking, or building agentic retrieval with knowledge bases.

microsoft/skills · 48 tokens

bf-to-agents-sdk-typescript-migration

Assess and migrate JavaScript or TypeScript bots from BotBuilder/Bot Framework SDK to Microsoft 365 Agents SDK with AgentApplication. Use to produce a migration report and plan before editing code, map BotBuilder packages and APIs, identify unsupported features, and implement only the supported plan items selected by…

microsoft/Agents · 71 tokens