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Game Creation with Codex and Claude Code

Game Creation With Codex And Claude Code — Aula 1: From Game Idea to Realistic Scope

Lo que aprenderas

  • The strongest first deliverable is a small, testable, agent-friendly game brief.
  • Write the loop in one sentence: Examples: match cards, jump over obstacles, click to earn points, or answer questions before time runs out.
  • Choose one player verb: Match, jump, click, answer, drag, or choose before adding any secondary systems.
  • **Think like a tester**: Define exactly what the player can do before asking an agent to build it.

What if your first browser game could begin with a clear brief and two strong agent plans? That is the goal of this lesson: not to build the biggest possible game, but to define a small, playable browser project that Codex and Claude Code can understand, plan, review, and help you finish.

Warning: Scope is a technical decision
Most first AI-assisted game projects do not fail because the idea is weak. They fail because the first version includes too many systems before the player can do anything fun.
50
AI video APIs were tested for one comparison platform, showing how tool choice can become a project by itself.
findaivideo.com

If 50 tools can exist just for one media category, imagine how quickly a game project can expand when you add physics, animation, enemies, inventory, saving, mobile controls, music, and online play. Your first job is to reduce the idea before asking an agent to build it.

From Idea to Buildable Brief

A game idea becomes buildable when it can answer four questions:

  1. What does the player do every few seconds?
  2. What counts as success?
  3. What screens are required?
  4. What should not be included in version one?

For a first browser game, your target is a playable loop, not a complete commercial product. Good first projects are small enough to explain on one page and test in a browser in minutes.

Tip: Before writing any code, describe the player action as a verb: click, dodge, match, drag, jump, answer, choose, or collect. If the verb is unclear, the project is not ready for an implementation prompt.

Why First Game Projects Break

A dangerous first project often sounds exciting:

  • Open world exploration
  • Real-time combat
  • Inventory and crafting
  • Multiplayer
  • Procedural maps
  • 3D enemies
  • Save files
  • Mobile controls
  • Dialogue trees

Each feature may be reasonable by itself. Together, they create a planning problem before you have a game.

A stronger first game starts with one mechanic and a clear finish line:

  • Match cards before time runs out
  • Jump over obstacles
  • Click to earn points and buy one upgrade
  • Answer 10 questions and receive a score
  • Drag objects into correct zones
  • Avoid falling shapes for 60 seconds
95 comments
A dosbox-staging issue requesting a very simple text editor closed after 95 comments, showing how small-sounding features can expand in requirements and debate.
dosbox-staging issue 2463

The lesson for game creators is direct: if behavior is not defined, even simple features expand. A “basic inventory” can become item categories, stacking rules, drag behavior, keyboard shortcuts, persistence, error states, and UI design. Define the feature before asking for code.

Good First Game vs. Dangerous First Game

Good First Game — Small scope

A good first game has one core mechanic, three or fewer screens, simple controls, visible feedback, and a testable win or loss condition. A lightweight browser prototype like Sprite Garden is a useful reference because it is visible, shareable, and understandable without becoming a large platform.

Dangerous First Game — High scope

A dangerous first game depends on multiple systems before the player can experience fun. If your first version needs inventory, combat, saving, mobile controls, complex animation, and multiple levels, the agents will spend most of their effort managing uncertainty instead of building a playable loop.

Deep Dive: Why Small Browser Games Work Well With Coding Agents

Browser games are strong first projects because the feedback loop is short. You can open the game locally, click through the interaction, inspect visible behavior, and ask an agent to make focused changes. HTML, CSS, and JavaScript also produce reviewable diffs. That matters because AI-assisted development is not only generation. It is planning, inspecting, testing, and revising.

Case Study: Sprite Garden

Sprite Garden is a small HTML Canvas 2D sandbox and farming project. It is a useful reference for a first browser game because it demonstrates the right kind of ambition: visible interactions, a simple world, and browser sharing.

You do not need to clone its features. You need to copy its discipline. It is not trying to become a full farming RPG in the first milestone. It gives the player something understandable to do.

Sprite Garden Example
Study a lightweight browser-based 2D sandbox as a realistic reference for first-game scope.

Pick One Core Mechanic

Your core mechanic is the repeated action that creates the game. It should fit in one sentence.

Good examples:

  • Match two cards with the same symbol.
  • Jump over obstacles and survive for 60 seconds.
  • Click objects before they disappear.
  • Answer questions before time runs out.
  • Drag ingredients into the correct basket.

Weak examples:

  • Explore a fantasy world and become powerful.
  • Build a complete RPG with combat and crafting.
  • Make a multiplayer survival game.
  • Create a 3D platformer with enemies and bosses.
Core Mechanic Test
My game is a browser game where the player [single verb] to [clear goal]. The first playable version is successful when [measurable outcome]. Exclude [features not in v1].
Use this template to reduce a vague idea into one playable loop before asking Codex or Claude Code for a plan.
Copy the prompt above and try it yourself
prompt
My game is a browser game where the player answers trivia questions to score 10 points before the timer ends.
The first playable version is successful when it runs locally, includes 10 questions, shows feedback after each answer, and displays a final score.
Exclude accounts, leaderboards, multiplayer, animations beyond basic transitions, and custom art generation.
Tip: If you cannot name the repeated player action, do not ask an agent to implement the game yet. Ask for help reducing the concept first.

Mini GDD: Eight Constraints Before Code

A mini GDD is a compact game design document. It should not be a 40-page design bible. For this course, use eight fields:

  1. Game idea
  2. Player goal
  3. Core loop
  4. Controls
  5. Rules
  6. Screens
  7. Visual and audio style
  8. Success criteria

Write the First Mini GDD

1
Define the player promise
State the game idea, player goal, and success criteria so the first milestone has a clear finish line.
2
Lock the playable loop
Describe the core loop, rules, and controls so Codex and Claude Code can reason about interaction flow.
3
Name the screens
List only the screens required for version one, such as start, game, and results.
4
Constrain media expectations
Decide whether the first version uses simple shapes, emoji-free text labels, placeholder sounds, or no audio.
5
Write success criteria
Define what must be true before you call the first milestone complete.

One-Page Game Brief Template

Use this structure before opening an implementation task.

One-Page Game Brief
Game idea: [one sentence]\nPlayer goal: [what the player tries to achieve]\nCore loop: [repeatable action sequence]\nControls: [mouse, keyboard, touch, or simple combination]\nRules: [3 to 6 rules]\nScreens: [start, game, results]\nVisual style: [simple, feasible browser visuals]\nAudio: [none, basic effects, or simple background loop]\nSuccess criteria: [measurable done state]\nOut of scope for v1: [features to reject]
Fill this out before asking either agent for code. The out-of-scope line is as important as the feature list.
Copy the prompt above and try it yourself
prompt
Game idea: A browser trivia game about climate facts.
Player goal: Score 10 points before the timer ends.
Core loop: Read question, choose answer, receive feedback, continue.
Controls: Mouse click or keyboard number keys.
Rules:
- One question appears at a time.
- Correct answers add 1 point.
- Wrong answers show the correct explanation.
- The game ends after 10 questions or when the timer reaches zero.
Screens: Start, game, results.
Visual style: Clean cards, high contrast, simple progress bar.
Audio: No audio in v1.
Success criteria: Runs locally, has 10 questions, no broken states, final score appears.
Out of scope for v1: Login, leaderboard, AI-generated questions, multiplayer, custom character art.
Warning: Do not hide uncertainty inside the prompt
If you are unsure about a rule, write it as an assumption to confirm. Do not let the coding agent invent core game behavior without review.

Codex Versus Claude Code: Agent Roles

Codex and Claude Code can both help with coding work, but you should assign them clear roles.

Codex — Depends on OpenAI plan

Use Codex for repository exploration, reviewable changes, diffs, test-focused edits, and code review. It is especially useful when you want an agent to inspect a project, understand existing files, propose scoped changes, and explain what changed.

Claude Code — Depends on Anthropic plan

Use Claude Code for local terminal iteration, architecture discussion, implementation planning, and working through a project interactively. It is useful when you want fast back-and-forth inside a local development workflow.

3 major coding-agent roles
This lesson separates planning, implementation, and review so that agents are not asked to design and build everything at once.
Lesson focus brief

The strongest workflow is not “ask one agent to make the whole game.” It is:

  1. Write the brief.
  2. Ask both agents for plans.
  3. Compare risks.
  4. Choose the smaller milestone.
  5. Implement one playable version.
  6. Review behavior against success criteria.

Master Planning Prompt for Both Agents

Before writing code, ask both agents for a plan. The wording matters: tell the agent not to implement yet.

Master Planning Prompt
Read this mini GDD. Do not write code yet. Identify assumptions, risks, files to inspect, and a small implementation plan. Keep the first milestone playable in the browser. Return tasks in order, with acceptance criteria for each task. Prefer the smallest architecture that can satisfy the brief.
Send this same planning prompt to Codex and Claude Code, then compare their assumptions before choosing an implementation path.
Copy the prompt above and try it yourself
prompt
Read this mini GDD. Do not write code yet.

Identify:
1. Assumptions that need confirmation
2. Scope risks
3. Files to inspect or create
4. A small implementation plan
5. Acceptance criteria for each task

Constraints:
- Keep the first milestone playable in the browser.
- Prefer simple HTML, CSS, and JavaScript unless the repository already uses a framework.
- Do not add multiplayer, accounts, databases, generated art, or complex animation.
- Return the plan first. Wait for approval before implementation.
Tip: Use the same planning prompt with both agents. If the agents receive different instructions, you are comparing prompts instead of comparing plans.

Validation Tools for Comparing Agent Plans

You need a way to compare outputs, not just generate them. These tools and resources help you evaluate agent plans more rigorously.

Yardstiq — See site

Yardstiq is a terminal tool for comparing LLM outputs side by side. In this lesson workflow, it supports asking multiple agents for implementation plans, then comparing assumptions, risks, and milestone size before coding.

LLMadness 2026 — Free evaluation resource

LLMadness is useful as an evaluation reference when thinking about model behavior. For a game project, the key habit is not choosing a winner blindly, but evaluating which plan is smaller, clearer, and easier to test.

AgentHub — Open source

AgentHub reflects a broader development pattern: when multiple AI systems are involved, consistent interfaces and validation matter as much as generation. Use it as a reference for thinking about repeatable agent workflows.

Shared Planning Prompt — Included in this lesson
The shared planning prompt is your control mechanism. It keeps Codex and Claude Code focused on assumptions, risks, files, tasks, and acceptance criteria before implementation begins.
64,312
GitHub stars for Scrapling, showing strong developer interest in automation tooling that can support research-heavy AI workflows.
Scrapling GitHub repository
23,789
GitHub stars for Crawlee, a TypeScript scraping and browser automation library positioned for AI, LLM, RAG, and GPT data extraction workflows.
Crawlee GitHub repository

These statistics are not about game design directly. They show a larger pattern: AI-assisted projects often depend on tool selection, automation, and validation. For your first game, do not let the tooling layer become larger than the playable loop.

How to Compare Two Agent Plans

When Codex and Claude Code return different plans, do not ask, “Which one sounds more impressive?” Ask, “Which one gets to a playable milestone with less risk?”

Use this review checklist:

  • Does the plan preserve one core mechanic?
  • Does it avoid unnecessary dependencies?
  • Does it define files to inspect or create?
  • Does it include acceptance criteria?
  • Does it keep media simple?
  • Does it identify assumptions?
  • Does it produce a browser-playable milestone?
Plan Comparison Prompt
Compare these two agent plans for the same mini GDD. Choose the smaller first milestone. Identify unnecessary complexity, missing assumptions, testing gaps, and the clearest acceptance criteria. Do not merge both plans unless the merged plan is still smaller than either original plan.
Use this after receiving separate plans from Codex and Claude Code. The goal is not compromise. The goal is a smaller playable milestone.
Copy the prompt above and try it yourself
prompt
Compare Plan A and Plan B for the same first browser game.

Evaluate:
- Smallest playable milestone
- Risk of scope creep
- Dependency complexity
- Testability in the browser
- Clarity of acceptance criteria
- Missing assumptions

Return:
1. Recommended plan
2. What to remove
3. What to implement first
4. What to test before adding features
Deep Dive: What To Do When Agents Disagree

Agent disagreement is useful. One plan may suggest a framework, state machine, asset pipeline, or component architecture. Another may suggest plain HTML, CSS, and JavaScript. For a first game, choose the architecture that creates the shortest path to a playable loop unless the existing repository already requires a framework. Architecture is not a trophy. It is a cost you pay to make change easier.

Write Success Criteria Before Code

Success criteria make the first milestone testable. Without them, the agent may keep adding features because “done” is undefined.

Bad success criteria:

  • Make it fun.
  • Add nice graphics.
  • Make the game polished.
  • Create a complete prototype.

Better success criteria:

  • The game runs locally in the browser.
  • The player can start, play, and finish one round.
  • There are 10 questions.
  • Correct and incorrect answers show feedback.
  • The result screen displays score and restart.
  • No console errors appear during normal play.
43 comments
An open Stella emulator issue about California Games not advancing past the BMX event had 43 comments, illustrating how game bugs need reproducible inputs and constrained fixes.
stella-emu issue 858

The Stella example is a reminder that game behavior needs reproduction steps. When you write your own success criteria, you are also writing the future bug report format.

Acceptance Criteria Prompt
Turn this game brief into testable acceptance criteria. Use checklist format. Include start state, main interaction, feedback, ending condition, restart behavior, and visible error states. Do not add new features.
Use this before implementation so the agent has a clear target and you have a practical review checklist.
Copy the prompt above and try it yourself
prompt
Turn this game brief into testable acceptance criteria.

Include:
- Start screen behavior
- Main interaction behavior
- Scoring rules
- Feedback after player input
- Ending condition
- Results screen
- Restart behavior
- Basic error states

Do not add new features.
Do not suggest future roadmap items unless they are clearly marked as out of scope.

Plan Before Implementation

The action sequence for this lesson is simple, but important.

Agent Planning Workflow

1
Write the brief
Use the mini GDD fields to define the first playable version.
2
Ask both agents
Send the same planning prompt to Codex and Claude Code without asking for code yet.
3
Compare risks
Look for assumptions, unnecessary dependencies, unclear screens, and missing success criteria.
4
Choose the smaller milestone
Approve only the plan that gets to a playable browser loop fastest.
5
Implement and review
Build the first version, then test it against the acceptance criteria before adding anything else.
Implementation Permission Prompt
Use the approved plan only. Implement the first playable milestone. Do not add features outside the brief. After implementation, summarize changed files, how to run the game, and which acceptance criteria are satisfied.
Use this only after you have reviewed the plans and chosen the smaller milestone.
Copy the prompt above and try it yourself
prompt
Use the approved plan only.

Implement the first playable milestone.
Do not add features outside the brief.

After implementation, report:
1. Changed files
2. How to run the game locally
3. Which acceptance criteria are satisfied
4. Any criteria not yet satisfied
5. Suggested next smallest improvement

Practice: Reduce a Game Idea

Take this vague idea:

“I want to make a cozy fantasy game where players collect creatures, explore different areas, upgrade their home, complete quests, and share progress online.”

A realistic first browser version could become:

“Make a browser collection game where the player clicks one of three zones, discovers a creature card, and tries to collect five unique creatures before running out of 10 turns.”

That reduced version has:

  • One core action: choose a zone
  • One resource: turns
  • One collection goal: five unique cards
  • Three screens: start, game, results
  • Simple visuals: cards and zones
  • No accounts, online sharing, inventory, or quests

Quiz: Which is the stronger first game project for AI-assisted development?

A 3D multiplayer RPG with crafting, quests, and combat
This has too many systems before the first playable loop is clear.
>> A browser trivia game with 10 questions, scoring, feedback, and a results screen
Correct. It has a clear loop, simple screens, and measurable success criteria.
An open world platformer with enemies, inventory, and save files
This combines several difficult systems and is risky for a first milestone.
A social farming game with accounts and online trading
Online systems add complexity that should not be in version one.

When the Two Agents Disagree

Sometimes Codex and Claude Code will recommend different architectures. For example, one may suggest a small React app, while another suggests plain JavaScript. One may suggest a state machine, while another suggests simple object state.

Do not decide based on which plan sounds more advanced. Decide based on the first playable milestone.

Quiz: If Codex and Claude Code recommend different architectures for your first small browser game, what should you do first?

Choose the more complex architecture because it may scale better
Scaling is not the first milestone. A first game needs a playable loop.
>> Ask both agents to justify risks, assumptions, files, and acceptance criteria before coding
Correct. Compare plans before implementation, then choose the smaller testable path.
Merge both plans into one larger plan
Merging often increases scope. Only merge if the result is still smaller and clearer.
Start coding immediately and fix architecture later
That can work for tiny experiments, but this lesson is about planning before implementation.
Tip: When in doubt, choose the plan with fewer moving parts and better acceptance criteria. You can improve architecture after the game exists.

Resources for This Lesson

One-Page Game Brief Template
Use this lesson’s mini GDD structure to define your first playable browser game before asking agents for code.
Writing Useful Game Design Documents
A video resource on turning a game idea into a practical design document.
How to Scope a Small Game
A focused video on reducing a game concept so you can actually finish it.
Stella Issue 858
A real game software bug discussion showing why reproduction steps and scoped fixes matter.
dosbox-staging Issue 2463
A real feature discussion showing how simple requests can expand when scope is not explicit.

Key Takeaways

The strongest first deliverable is not code. It is a small, testable, agent-friendly game brief.

A good first browser game has one core mechanic, a few screens, simple controls, constrained media expectations, and measurable success criteria. Codex and Claude Code become much more useful when you ask them to plan before implementing.

5 videos
The provided lesson research includes confirmed videos about game ideas, GDDs, roadmaps, and small-game scope.
Provided YouTube video list

Your next step is to set up the project and agent workflow. In the next lesson, you will move from brief to working environment, then use the USD 10 course workflow to build toward a playable first browser game with disciplined scope.

Materiales de practica y visuales

Estos recursos complementan la leccion escrita y sirven para repasar, practicar o reutilizar la clase.

Entregables

Infografias

!50

!Good First Game vs. Dangerous First Game

!95 comments

!Mini GDD: Eight Constraints Before Code

!Codex Versus Claude Code: Agent Roles

!Validation Tools for Comparing Agent Plans

!43 comments

!Plan Before Implementation

!The strongest first deliverable is a small, testable, agent-friendly game brief.

Logos y referencias visuales

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