# Gemini AI > Gemini API integration for generating pedagogically-grounded game questions from lesson content - Skill: `seanchiuai/gemini-ai` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add seanchiuai/gemini-ai` - Raw SKILL.md: https://api.skillmd.com/api/skills/seanchiuai/gemini-ai/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Integrations & APIs - Author: seanchiuai (https://skillmd.com/u/seanchiuai) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/seanchiuai/gemini-ai --- # Gemini AI Handles the two-step AI generation pipeline — the core differentiator of LessonPlay. Gemini processes lesson content + learning objectives to produce (1) structured questions and (2) a self-contained HTML game that runs in a sandboxed iframe. ## Overview - **SDK**: `@google/genai` npm package (`GoogleGenAI` class) - **Input**: Lesson text content + learning objective + objective type - **Step 1 Output**: 8-10 structured questions as JSON (for scoring/analytics) - **Step 2 Output**: Self-contained HTML game (inline CSS/JS, no external deps) that renders the questions - **Key**: Questions test understanding, not recall. Games are unique every time. - **Format**: Step 1 uses structured JSON output; Step 2 uses plain text (HTML string) ## When to Use This Skill - Building or modifying the two-step generation pipeline - Engineering or iterating on the question generation prompt - Engineering or iterating on the HTML game generation prompt - Parsing and validating Gemini's structured output - Validating generated HTML (postMessage protocol, no external URLs) - Handling generation errors or retries - Mapping objective types to question/game formats ## Key Concepts ### SDK Usage ```typescript import { GoogleGenAI } from "@google/genai"; const ai = new GoogleGenAI({ apiKey }); const response = await ai.models.generateContent({ model, contents, config }); const text = response.text; // property, NOT a method ``` ### Structured Output Use `config.responseMimeType: "application/json"` and `config.responseSchema` to enforce JSON structure. The SDK handles schema validation — no need to manually parse or hope for correct formatting. ### Objective Type → Question Format Mapping | Objective Type | Preferred Question Types | |----------------|------------------------| | Understand | Multiple choice (concept questions) | | Explain | Multiple choice (why/how questions) | | Apply | Multiple choice (scenario-based) | | Distinguish | Categorization (sort into groups) | | Perform | Ordering (sequence steps) | | Analyze | Multiple choice + categorization | ### Calling from Convex Gemini calls MUST happen in a Convex **action** (not query or mutation). Use `ctx.runMutation(internal.xxx.yyy, args)` to store results in the database. ### Question Quality Markers - Tests understanding over recall - Wrong answers are plausible misconceptions, not random - Explanation teaches, not just confirms - Question maps to the stated learning objective ### HTML Game Generation Requirements The generated HTML must: - Be a complete `` document with inline `