Building A Plasma Sword Fighter Game with Amazon Q CLI

As a DevSecOps engineer, my daily grind usually involves CI/CD pipelines, security audits, and infrastructure as code. So, when the "Build Games with Amazon Q CLI" campaign popped up, it was a refreshing detour from the usual. The idea of conjuring a game with just conversational prompts, powered by Amazon Q CLI's Claude 4 large language model, was too intriguing to pass up. This isn't the usual realm of an "enthusiast" for me, but more of an exploration into how AI can augment a developer's toolkit, even outside their primary domain.

The Game: A "Space Trilogy" Inspired Plasma Sword Fighter ✨

My concept for the game was heavily inspired by the classic "Space Trilogy" narratives (you know the ones 😉), where the good guys wield blue "light swords" and the antagonists opt for menacing red ones. I wanted to capture that classic duel vibe, with players having supernatural "force push" abilities to add another layer to the combat. The result is a "Plasma Sword Fighter" game – a two-player combat experience featuring real-time sword mechanics and tactical force pushes. It's designed to be intuitive, visually engaging, and, importantly, free from copyright entanglements by using generic names.

Effective Prompting: Speaking the AI's Language 🗣️

My interaction with Amazon Q CLI was a rapid learning curve in effective prompting. Here’s what I found worked best:

Context is King: I started by setting the scene: "write a pygame on a streetfight style of star war light sword game, but don't use real names to avoid copyright." This broad stroke gave the AI its initial direction.

Feature by Feature: Instead of overwhelming the AI with a massive request, I let the AI to design an initial version first, followed by my later bug requests as well as feature enhancements, this allowed the AI to build the game incrementally.

Leveraging Error Messages: When things inevitably went sideways (as they do in development 🐛), I found Amazon Q CLI doing a good job on auto-identifying the errors from the command outputs in its initial runs, and it was able to resolve the errors by itself without my intervention.

Refining Game Logic: One of the more nuanced challenges was ensuring continuous damage when an opponent remained in the sword's active area. My prompt, "now there's a problem, the opponent's HP doesn't decrease for a 2nd time if the opponent stayed in the attack area of the plasma sword. resulted in You're right! The issue is that the combat detection only triggers once per attack due to the last_hit_time check. When a player holds down the attack button and the opponent stays in range, it should continue dealing damage. Let me fix this:", guided Amazon Q CLI to implement a time-based hit detection, allowing for sustained damage while preventing hit-spamming with invulnerability frames.

AI as a Development Accelerator / Quick Prototype Generator ⚡

Amazon Q CLI, recently powered by Claude 4, proved to be an invaluable development partner. It automated much of the heavy lifting, significantly reducing my development time:

• Boilerplate Generation: The initial pygame setup, including window creation, basic event loops, and constant definitions, was generated almost instantly. This freed me from the mundane setup tasks.
• Core Game Mechanics: From player movement and sword activation to force push mechanics and health management, the AI took my high-level descriptions and translated them into functional code.
• Smart Debugging: The AI's ability to not only identify errors but also suggest and implement fixes, like installing missing libraries or correcting logical flaws in combat detection, was a major time-saver.
• Iterative Refinement: The back-and-forth process of prompting, testing, and refining allowed for quick iterations and continuous improvement of the game's mechanics.

About the Code 💻

The Python code for the "Plasma Sword Fighter" game is straightforward and relies solely on the pygame library. While some of the combat and AI logic might appear "raw" to a seasoned game developer, offering room for more sophisticated refactoring (e.g., using state machines for AI), the current structure is remarkably readable. This clarity is a testament to the AI's ability to produce understandable code, even when generating complex interactions.

The full code is be hosted on GitHub here: https://github.com/gabrielkoo/amazonq-plasma-sword-fighter-game/

Screenshots and Gameplay 🎮

Here are some snapshots from the "Plasma Sword Fighter" battles:

• Ready for Battle: The game's initial screen, featuring two fighters against a cosmic backdrop, their health bars poised for action.
• Mid-Combat: A dynamic shot showing the glowing plasma swords in action, with players engaged in a fierce duel.

Game Features:

• Two-player combat with glowing plasma swords (avoiding copyright)
• Real-time combat system with sword swinging and blocking
• Supernatural "force push" ability with cooldown mechanics
• Health system with visual health bars
• Invulnerability frames after taking damage
• Visual effects including sword glow and hit flashes
• Starfield background for an immersive space combat feel
• AI opponent with adjustable difficulty (Easy, Medium, Hard)

How to Play:

• Player 1 (Blue): WASD to move, SPACE to activate sword, SHIFT to attack, Q for force push, T to toggle targeting mode (mouse vs. auto-target).
• Player 2 (Red): Arrow keys to move, Right CTRL to activate sword, Right SHIFT to attack, ENTER for force push, P to toggle targeting mode (mouse vs. auto-target).
• AI Difficulty: Press 1 for Easy, 2 for Medium, 3 for Hard.

Combat Mechanics:

• Activate your plasma sword and maneuver close to your opponent.
• Swing your sword to deal damage (10 HP per hit).
• Utilize force push to knock back enemies and inflict minor damage (5 HP + knockback).
• Each player starts with 100 HP; the first to reach 0 loses.
• Brief invulnerability periods after taking damage prevent spam attacks.

Game Controls:

• Press R to restart after a game over.
• Press ESC to quit anytime.

The "Plasma Sword Fighter" game captures the essence of classic space duels without infringing on any existing intellectual property. The visual effects create that iconic glowing sword aesthetic, offering a fun and engaging combat experience.

Final Thoughts 💡

This experience with Amazon Q CLI wasn't just about building a game; it was about understanding the practical applications of GenAI in accelerating software development. Amazon Q CLI, recently leveraging Claude 4, is a powerful tool that can significantly enhance productivity, even for those working outside traditional software development domains. It's a clear example of how GenAI can democratize development, allowing anyone with an idea to bring it to life with guided assistance. I'm genuinely impressed and encourage others to experiment with Amazon Q CLI to discover its potential firsthand.