GridyPig Quiz Clash: Turning Prompts into Multiplayer Games with Hermes Agent

--- title: "GridyPig Quiz Clash: Turning Prompts into Multiplayer Games with Hermes Agent" published: true tags: hermesagentchallenge, devchallenge, agents, game --- *This is a submission for the [Hermes Agent Challenge](https://dev.to/challenges/hermes-agent-2026-05-15)* ## What I Built I built **GridyPig Quiz Clash**, an agent-assisted quiz creation and multiplayer game mode inside GridyPig, a multi-tenant real-time game platform. The problem I wanted to solve is simple: creating a good quiz for an event, launch party, classroom, community night, or team activity is slow. A creator has to plan the topic, write questions, balance difficulty, avoid repeating old material, validate answer options, and then turn everything into something people can actually play together. GridyPig Quiz Clash turns that into a much faster flow: 1. A creator describes the quiz they want in plain English. 2. Hermes Agent plans the quiz structure and checks the existing reusable quiz bank. 3. Hermes avoids duplicate or repeated questions, balances difficulty, and returns generation notes with validated questions. 4. GridyPig normalizes the output into a playable quiz set. 5. The creator can edit, collapse, import, dictate, save, and launch the quiz as a live multiplayer room. The result is not just generated text. It is an agent-assisted path from creator intent to a playable real-time game. ## Demo Demo link: https://www.loom.com/share/4092af7b2920444984bcdc73a5363cab Recommended demo path: 1. Open a tenant workspace, for example `https://justin.gridypig.com`. 2. Create or sign in as a player/creator. 3. Start a new game and choose **Quiz Clash**. 4. Use the **AI quiz builder** prompt, for example: ```text Create a fun 8-question quiz about Nigerian tech startups for a launch party. Mix simple and tricky questions. ``` 5. Show the generation button moving through planning, quiz-bank checking, duplicate avoidance, difficulty balancing, and formatting stages. 6. Show Hermes generation notes explaining the plan, bank check, duplicate avoidance, and validation checks. 7. Save the quiz set and open a live room. 8. Join with another player or show the simulation/live room flow. 9. Play through a few turns and show the final leaderboard. Screenshots/video placeholders: - Game landing page  - Quiz Builder with Hermes Agent  ## Code Repository: [github.com/cjustinobi/greedy-pig](https://github.com/cjustinobi/greedy-pig) Key areas: - Hermes Cloud Run adapter: `deploy/hermes/` - Backend quiz generation service: `apps/backend/src/quiz/quiz-ai.service.ts` - Quiz APIs and reusable quiz bank: `apps/backend/src/quiz/` - Frontend quiz setup UI: `apps/frontend/src/components/quiz/` - Real-time game room: `apps/frontend/src/components/game/` ### My Tech Stack - **Frontend:** Next.js, React, Tailwind CSS, Framer Motion - **Backend:** NestJS, Prisma, PostgreSQL/Supabase - **Realtime:** Socket.io - **Agent Runtime:** Hermes Agent behind an OpenAI-compatible Cloud Run adapter - **Infrastructure:** Google Cloud Run, Docker, Vercel, GitHub Actions - **Product Layer:** Multi-tenant workspaces, PWA support, referral system, reusable quiz bank, wallet-aware game modes ## How I Used Hermes Agent Hermes Agent powers the quiz creation layer. I wrapped Hermes in a small Cloud Run service that exposes an OpenAI-compatible `/v1/chat/completions` endpoint, so the GridyPig backend can swap AI providers without coupling the game engine to a specific model vendor. The flow: ```text Creator prompt -> Hermes plans quiz structure -> Hermes checks existing quiz bank -> Hermes avoids duplicate/repeated questions -> Hermes balances difficulty -> Hermes returns generation notes + validated questions -> GridyPig saves playable quiz set ``` ### 1. Prompt-to-Playable Structured Output GridyPig does not need a paragraph of generated text. It needs valid game data. Hermes receives the creator's intent and returns a strict schema: ```json { "plan": "Short generation plan", "difficultyBalance": "How the quiz difficulty was balanced", "avoidedDuplicates": ["Bank question or duplicate pattern avoided"], "qualityChecks": ["Validation checks performed"], "questions": [ { "prompt": "Question text", "type": "MULTIPLE_CHOICE", "options": ["A", "B", "C", "D"], "correctAnswers": ["A"], "difficulty": "MEDIUM", "explanation": "Why the answer is correct" } ] } ``` The backend then validates and normalizes the output before it ever reaches gameplay. If a question is malformed, it is rejected instead of silently breaking the room. ### 2. Quiz-Bank Awareness Before calling Hermes, GridyPig samples relevant reusable questions from the tenant and shared quiz bank. That context is passed into the agent as `existingBankSample`. Hermes is instructed to review that sample, avoid exact duplicates, avoid close paraphrases, and explain what it avoided in `avoidedDuplicates`. This makes the quiz pool feel fresher over time instead of repeatedly generating the same obvious questions. ### 3. Generation Notes for Trust The UI now shows Hermes generation notes after questions are generated: - The quiz plan. - The difficulty-balancing strategy. - What existing bank questions or duplicate patterns were avoided. - The validation checks Hermes performed. This gives the creator confidence that the agent did more than return a blob of questions. ### 4. Agent Adapter Built for Production Constraints Hermes Agent runs as its own Cloud Run service. During testing I hit real deployment issues: container startup, Cloud Run port binding, long-running agent loops, and noisy CLI output around JSON. I solved this by building a dedicated adapter that: - Listens on Cloud Run's `PORT` correctly. - Secures requests with a shared secret between the backend and Hermes service. - Uses ephemeral runtime state so the agent does not hang on Cloud Storage/FUSE SQLite WAL files. - Bounds generation to a single quiet chat turn for predictable response time. - Extracts clean quiz JSON even when the CLI returns session noise or markdown wrappers. That adapter made Hermes usable as a real service, not just a local experiment. ### 5. Human-in-the-Loop Creation I intentionally kept the creator in control. Hermes accelerates quiz creation, but the creator can still: - Edit every generated question. - Choose predefined or custom categories. - Pick question type: yes/no or multiple choice. - Use voice dictation for questions and options. - Import questions from a template. - Save questions into a reusable quiz bank. - Search and reuse existing quiz questions later. This matters because a great quiz is partly AI generation and partly human taste. Hermes gets the creator most of the way there, then GridyPig gives them tools to polish the final game. ## What Makes It More Than a Quiz Generator The generated quiz becomes part of a full multiplayer game system: - **Turn-by-turn Quiz Clash:** players answer in sequence and the highest score wins. - **GridyPig streak mode:** correct answers can keep a player in control, preserving the push-your-luck feel of the original game. - **Server-side validation:** scoring and turns are enforced by the backend, not trusted to the browser. - **Inactivity countdowns:** if a player stalls, the room warns everyone and passes the turn safely. - **Draw handling:** tied zero-score quiz games end as draws instead of arbitrarily picking the creator. - **Final standings:** the game ends with a leaderboard showing how each participant performed. - **Tenant workspaces:** each business/community can run its own branded games. - **Reusable quiz bank:** creators can build from scratch or reuse questions over time. ## What I Learned The biggest lesson was that agentic features need product boundaries. It is tempting to let an agent do everything, but a real-time game needs deterministic behavior. Hermes is excellent at helping create the content, but the platform still needs strict validation, typed payloads, server-side scoring, and predictable fallback behavior. So the winning architecture became: ```text Creator intent -> Hermes Agent planning and bank-aware generation -> Structured quiz draft with generation notes -> Backend validation -> Human editing -> Live multiplayer game ``` That separation keeps the AI useful without letting it destabilize the game loop. ## What's Next I want to expand the Hermes layer from quiz generation into a full game-master assistant: - Suggest better distractor options for weak multiple-choice questions. - Rebalance difficulty based on historical answer rates. - Generate themed quiz packs for events, product launches, schools, and community nights. - Help creators convert reusable quiz-bank content into polished game sessions. - Create post-game summaries that explain what players struggled with and what they learned. GridyPig started as a dice game. With Hermes Agent, it is becoming a creator-powered game platform where anyone can turn an idea into a live multiplayer experience.