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Use when integrating Google Gemini API into projects. Covers model selection, multimodal inputs, streaming, function calling, and production best practices.
Passed 22 of 23 test cases with the skill, and 12 of 23 without it.
and 10 more in the full report
10 fixed12 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
I am starting a new Python project to interact with Google's generative models. We usually install `google-genai` and set `GOOGLE_API_KEY`. What is the specific library package and exact environment variable name required by the generative AI SDK?
| Checked | Without skill | With skill |
|---|---|---|
| Instructs to install google-generativeai. | Missed | Passed |
| Specifies setting GEMINI_API_KEY. | Passed | Passed |
The instructions your model reads when the skill loads.
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.
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"
Node.js:
import { GoogleGenerativeAI } from "@google/generative-ai";
test cases passed, vs 12 / 23 without
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