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jev-clash-royale-test

Node.js Clash Royale-style sandbox where a Jev bot decides play or hold, card, lane and depth in one call, versus an Ollama LLM bot.

Libraryprototype

Overview

Node Royale is a minimal real-time Clash Royale-style game engine in Node.js for comparing decision models with generative LLMs as game controllers. It includes a TypeSafe Jev bot, an Ollama LLM bot that uses traditional prompt-and-parse, an MCP server with standardised tool endpoints for external agents, and a canvas web client to play against the bots live.

The Jev bot first filters its hand by current elixir in code, then makes a single System One request with parallel judgments: a Noul for whether to play now, a Choice of card among affordable cards plus hold, a Choice of lane, and a Choice of placement depth (bridge, mid or back). A code policy engine banks elixir and waits on hold or low confidence, and otherwise posts a move that is always legal. The README contrasts this with the LLM bot's multi-second latency, arguing generative models are unsuited to twitch reflexes.

What the decision model decides

TypeQuestionAnswers
Yes / noShould the bot play a card now?yes · no
ChoiceWhich affordable card (or hold)?—
ChoiceWhich lane?lane 0 · lane 1
ChoiceWhere to place it?bridge · mid · back

How it works

  1. Code filters the hand by elixir
  2. One Jev request answers play, card, lane and depth
  3. Policy engine holds on low confidence
  4. Post a legal action to the game

Strengths

  • Every action is legal by construction
  • Side-by-side comparison with an LLM bot
  • MCP endpoints for external agents

Caveats

  • Toy game engine
  • No licence stated

Getting started

`npm install`, then start the server and open the canvas client per the README.

At a glance

Type
Library
Status
prototype
Language
JavaScript
Runtime
Node game server, browser client, MCP
Has code
yes

Use cases and integrations

How curated lists describe it

Frequently asked questions

What does Jev decide?

Whether to play, which card, which lane and how deep, all in one call.

How is it compared?

Against an Ollama LLM bot using prompt-and-parse.

Can external agents play?

Yes, through the MCP server.

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