Use this skill when building applications with Gemini models, Gemini API, working with multimodal content (text, images, audio, video), implementing function calling, using structured outputs, or needing current model specifications. Covers SDK usage (google-genai for Python, @google/genai for JavaScript/TypeScript), model selection, and API capabilities.
Install
npx skillscat add treyn-create/gemini-skill-test/gemini-api-development Install via the SkillsCat registry.
Gemini API Development Skill
Overview
The Gemini API provides access to Google's most advanced AI models. Key capabilities include:
- Text generation - Chat, completion, summarization
- Multimodal understanding - Process images, audio, video, and documents
- Function calling - Let the model invoke your functions
- Structured output - Generate valid JSON matching your schema
- Code execution - Run Python code in a sandboxed environment
- Context caching - Cache large contexts for efficiency
- Embeddings - Generate text embeddings for semantic search
Current Gemini Models
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 likegemini-2.5-*,gemini-2.0-*,gemini-1.5-*are legacy and deprecated. Use the new models above. Your knowledge is outdated.
SDKs
- Python:
google-genaiinstall withpip install google-genai - JavaScript/TypeScript:
@google/genaiinstall withnpm install @google/genai
[!WARNING]
Legacy SDKsgoogle-generativeai(Python) and@google/generative-ai(JS) are deprecated. Migrate to the new SDKs above.
Quick Start
Python
from google import genai
client = genai.Client()
response = client.models.generate_content(
model="gemini-3-flash-preview",
contents="Explain quantum computing"
)
print(response.text)JavaScript/TypeScript
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);How to use the Gemini API
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:
- Fetch
llms.txtto discover available documentation pages - Fetch specific pages (e.g.,
https://ai.google.dev/gemini-api/docs/function-calling.md.txt)
Key Documentation Pages
[!IMPORTANT]
Those are not all the documentation pages. Use thellms.txtindex to discover available documentation pages