🤖 Skill: gemini-sdk-expert (v1.3.0)

Executive Summary

gemini-sdk-expert is a high-tier skill focused on mastering the Google Gemini ecosystem. In 2026, building with AI isn't just about prompts; it's about Structural Integrity, Context Optimization, and Multimodal Orchestration. This skill provides the blueprint for building ultra-reliable, cost-effective, and powerful AI applications using the latest @google/genai standards.

📋 Table of Contents

1. [Core Capabilities](#core-capabilities)
2. [The "Do Not" List (Anti-Patterns)](#the-do-not-list-anti-patterns)
3. [Quick Start: JSON Enforcement](#quick-start-json-enforcement)
4. [Standard Production Patterns](#standard-production-patterns)
5. [Advanced Agentic Patterns](#advanced-agentic-patterns)
6. [Context Caching Strategy](#context-caching-strategy)
7. [Multimodal Integration](#multimodal-integration)
8. [Safety & Responsible AI](#safety--responsible-ai)
9. [Reference Library](#reference-library)

🚀 Core Capabilities

• Strict Structured Output: Leveraging responseSchema for 100% reliable JSON generation.
• Agentic Function Calling: enabling models to interact with private APIs and tools.
• Long-Form Context Management: Using Context Caching for massive datasets (2M+ tokens).
• Native Multimodal Reasoning: Processing video, audio, and documents as first-class inputs.
• Latency Optimization: Strategic model selection (Flash vs. Pro) and streaming responses.

🚫 The "Do Not" List (Anti-Patterns)

⚡ Quick Start: JSON Enforcement

The #1 rule in 2026: Structure at the Source.

import { GoogleGenerativeAI, Type } from "@google/genai";

// Optional: Set API Version via env
// process.env.GOOGLE_GENAI_API_VERSION = "v1beta1";

const schema = {
  type: Type.OBJECT,
  properties: {
    status: { type: Type.STRING, enum: ["COMPLETE", "PENDING", "ERROR"] },
    summary: { type: Type.STRING },
    priority: { type: Type.NUMBER }
  },
  required: ["status", "summary"]
};

// Always set MIME type to application/json
const result = await model.generateContent({
  contents: [{ role: 'user', parts: [{ text: "Evaluate task X..." }] }],
  generationConfig: {
    responseMimeType: "application/json",
    responseSchema: schema
  }
});

🛠 Standard Production Patterns

Pattern A: The Data Extractor (Flash)

Best for processing thousands of documents quickly and cheaply.

• Model: gemini-3-flash
• Config: High topP, low temperature for deterministic extraction.

Pattern B: The Complex Reasoner (Pro)

Best for architectural decisions, coding assistance, and deep media analysis.

• Model: gemini-3-pro
• Config: Enable Strict Mode in schemas for 100% adherence.

🧩 Advanced Agentic Patterns

Parallel Function Calling

Reduce round-trips by allowing the model to call multiple tools at once. See [References: Function Calling](./references/function-calling.md) for implementation.

Semantic Caching

Store and retrieve embeddings of common queries to bypass the LLM for identical requests.

💾 Context Caching Strategy

In 2026, we don't re-upload. We cache.

• Warm-up Phase: Initial context upload.
• Persistence Phase: Referencing the cache via cachedContent.
• Cleanup Phase: Managing TTLs to optimize storage costs.

See [References: Context Caching](./references/context-caching.md) for more.

📸 Multimodal Integration

Gemini 3 understands the world visually and audibly.

• Video: Scene detection and temporal reasoning.
• Audio: Sentiment, tone, and environment detection.
• Document: Visual layout and OCR.

See [References: Multimodal Mastery](./references/multimodal-2026.md) for details.

📖 Reference Library

Detailed deep-dives into Gemini SDK excellence:

• [Structured Output](./references/structured-output.md): Nested schemas and validation.
• [Function Calling](./references/function-calling.md): Tools, execution loops, and security.
• [Context Caching](./references/context-caching.md): Reducing cost and latency.
• [Multimodal 2026](./references/multimodal-2026.md): Video, audio, and PDF mastery.

Updated: January 31, 2026 - 10:45