Point your AI agent at almost any PC game you own and watch it reverse engineer, mod, test and film the result. 🔗 rehan-remade/universal-modder
Credits: rehan-remade/universal-modder
#universalmodder #python #gamemodding
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AI Game Mashups: Can AI Really Turn Two Games Into One?
Mario shooting some baddies in Halo. Minecraft inside GTA V ([see Appendix: a real-world example](#appendix-a-real-world-example)). A social media trend has people sharing videos of what’s being branded as “AI game mashups.” The claim is that people have used AI to reverse engineer different games and mash them together into one in unexpected or cool ways... but is that the whole story?
As usual, hype has a tendency to exaggerate things to create, well, more hype. So let's separate reality from fiction and explore what’s actually happening behind these demos.
The good news is that there is plenty on the reality side to be mind-blown about! However, there are also some disappointing truths. At least for the time being.
Let's Mash Candy Crush And Call of Duty!
Let's walk through a ridiculous combination as a practical example. Let's imagine that we want to combine Candy Crush and Call of Duty!
However, simply naming two games does not constitute a plan. Like anything else, first we need to work out our requirements and architectural concerns.
Here's my take: every time you reload your weapon, Candy Crush loads inside the Call of Duty gameplay and you have to complete a match-three puzzle before the reload can finish.
!Concept illustration of a match-three puzzle overlay interrupting a first-person shooter reload.
Hypothetical mashup: solve a match-three puzzle to finish reloading. AI-generated concept illustration, not a screenshot of a working mod.
I have no idea whether that would be fun. I suspect my teammates would have opinions. But at least we now have something concrete enough to discuss.
There are still decisions to make though. Does the shooter pause while you solve the puzzle? What happens if you fail? Can you cancel? Does a harder puzzle earn you more ammunition?
Neither original game contains the answers so it's up to us to introduce new rules.
And that is our first lesson: Connecting two game engines does not automatically create coherent new gameplay. Somebody, potentially with AI assistance, still has to decide what the connection means and implement it.
What Are We Actually Mashing Together?
When I watch these demos, I find it useful to separate four things.
| What’s happening | What it establishes |
| --- | --- |
| Visual composition | Images or rendered objects from different sources appear together. |
| Event integration | Something happening in one game triggers something in another. |
| Gameplay orchestration | New rules coordinate actions and state across the games. |
| Hybrid game design | Those rules form a coherent experience with its own objectives, constraints and balance. |
These can overlap. A project might combine graphics and translate a few events without sharing every part of either simulation.
For example, an explosion in one game could trigger an explosion in another. That is a meaningful integration, but it doesn’t, by itself, establish that every object in both worlds can collide, that both physics engines agree, or that every mission works across the boundary.
A clip can still demonstrate a specific interaction beautifully while leaving those broader questions unanswered.
The missing interfaces
Ok, so how can we go about implementing our Call of Duty and Candy Crush mash-up? Well, to begin with we need to discover each game's available integration points. Then we need to find a way to connect those before finally figuring out how to coordinate the result.
1. Find a way to control the relevant behaviour
A game with a supported modding API might already expose the events and controls we need. Otherwise, investigating its internal behaviour may be necessary.
For our shooter, we would need to identify a reload request and find a reliable way to defer it. For the puzzle, we need to start a challenge and detect its completion. Observing an animation on screen is different from having a dependable signal that the underlying action succeeded.
This is where reverse engineering can contribute: working out how software behaves when its original source code or a suitable interface isn’t available.
REA, or Reverse Engineer Anything, is one project in this area and the one behind the viral game mashups trend. Its documentation describes connecting agents to analysis tools, including Ghidra, Hopper and IDA, and returning findings that an agent can investigate further.
It is indeed a pretty cool tool that gives an agent ways to inspect software. However, it is NOT a magical command that enables agents to recover an entire game’s original source project or to understand every subsystem.
Moreover, it's important to remember that runtime modification of games predates AI tools.
Mod Engine 2, for example, documents runtime patching and injection for Souls games, including Elden Ring.[3] Existing tools and community knowledge are part of the foundation here.
2. Build interfaces between the games
Once we understand the relevant behaviour, we can build adapters: code that translates between what our mashup needs and what each game can actually do.
From the coordinating code’s perspective, the shooter adapter might offer operations such as “defer reload” or “resume gameplay.” The puzzle adapter might offer “start challenge” and a completion event.
Those are interfaces that we have to build unless the game itself provides out-of-the-box integration points, or in simpler language, hooks. This could be, for example, official support for mods. That means creating and maintaining your own adapter code, which, yes, you can also use AI to help you generate.
There is an added complication: If components run in separate processes, they need a way to exchange messages, such as sockets or named pipes. This is referred to as inter-process communication, often shortened to IPC.
A hook and a communication channel have different jobs. A hook can intercept behaviour inside a game whereas IPC lets separate processes exchange information. Having one doesn’t automatically give us the other.
Either way, we arrive at our second lesson: AI doesn't somehow make two incompatible executables magically understand each other. The real magic is that AI can help us build the missing interfaces between them.
3. Implement the new rules
Now we need the coordinator, or orchestrator, that implements our reload rule so we can load Candy Crush every time you need to reload your weapon on Call of Duty.
Here's the plan: it receives a reload request, defers the action, puts the shooter into an appropriate paused state, and opens the puzzle. On success, it allows the reload to proceed and returns control to the shooter.
!Flow diagram showing the reload request, deferred reload, paused shooter, puzzle outcome, and success or recovery paths.
The orchestrator coordinates the reload and puzzle, with a recovery path for failure, cancellation or timeout. This conceptual flow assumes the required integration points exist.
What if the puzzle crashes though? The player shouldn’t remain trapped forever with a frozen gun. And how about if a completion message arrives twice? We need to be careful not to grant ammunition twice. Like any piece of software we need to design for our error conditions.
This is why “pause the game” deserves scrutiny. Preventing player input is different from pausing the simulation. In a networked game, the server and other players may continue regardless. Our example depends on capabilities that may be unavailable or prohibited in a protected online title.
If you work with microservices, there’s a familiar architectural idea here. Connecting two services doesn’t automatically create an e-commerce application. You still need rules that define what placing an order means, what happens next, and how failure is handled.
Games add another difficulty, one that becomes our third lesson: we still need to design and build gameplay rules for the mashup much like building any other game.
Do the games become one program?
They don’t have to.
In one possible implementation of our example, the shooter and puzzle remain separate processes while our own coordinator manages their behaviour and presentation.
The simplest implementation may be, for example, switching back and forth between the Candy Crush puzzle’s window and the Call of Duty window. A more integrated version could display the puzzle within the shooter’s view as ensioned in our concept above. We'll have to work harder for it because it then adds rendering and input-routing work but it does look super cool. Either way, the objective is to have the player experience a single set of rules while multiple programs do the work.
Another consideration is whether we need to create our own launcher app. This could gives even more control over the runtime and coordination between the two processes running either game, however it does not automatically give control over either game's internals.
So lesson four is: the desired user experience dictates how much control you need to have over either game and determines the architectural choices as well as the amount of code that you need to write and maintain.
Where did the graphics come from?
This is perhaps the most intriguing question.
A newly written game might use original artwork, generated assets, placeholders or reused material. A mod might leave the original game’s engine and assets in place. A mashup might combine output from two running engines, each rendering its own content.
Those are different workflows. A familiar character on screen doesn’t tell you which one happened.
In our hypothetical example, if both original games were running, neither would need its graphics recreated merely to appear in the experience. Each game already knows how to render its own world. The integration challenge would concern control, communication, presentation and the new rules.
Conversely, reproducing familiar graphics in a newly written program doesn’t establish that the original physics, enemy behaviour, timing or levels have been reproduced.
But hang on. If we put Mario inside Halo, how does he know where the floor is? Doesn’t he come with his own bounding box? The important distinction is that a character’s appearance and its collision behaviour are separate things. A visible model doesn’t automatically bring a working physics system with it.
For a hypothetical model replacement, we could give an existing Halo character Mario’s appearance while keeping the host character’s movement and collision setup. Or, if we were adding a new character, we would need to create or convert the collision data into a form the host engine understands and configure its behaviour. Halo wouldn’t need to recognise “Mario”; it would need a correctly configured character in its own simulation. That could stop him falling through the floor without reproducing how he moves in a Mario game.
So lesson number five is: Looking like two worlds have merged does not mean that their physics have merged too. There's work to be done to make that happen.
Asset provenance and permission are also separate questions from whether an integration works. A clip alone cannot answer them. Before making claims about how a creator obtained the assets, we need their documentation.
Where does the AI fit?
We should distinguish AI helping build the mashup from AI running it.
During development, an agent can use tools to investigate behaviour, propose integration code and help iterate on failures. REA’s documented workflow, for example, lets an agent inspect findings, ask follow-up questions, and write and test an implementation.[2]
But once our reload rule works, it can run as ordinary deterministic code. Receive the event, start the puzzle, wait for a result, update the state. There is no inherent need to ask a language model what should happen every time the player reloads.
AI can be the engineer that builds the bridge without being the driver that crosses it.
That distinction also helps us evaluate claims about speed. A successful demo shows that someone achieved a result. Understanding how much AI accelerated it requires more evidence: the starting tools, existing mods, development history, human interventions and failed attempts. The finished clip doesn’t contain that history.
Appreciate the demo. Be precise about the claim.
I find this trend exciting because it opens up questions about what people might build when investigating and connecting unfamiliar software becomes more accessible. Not to mention that level of creativity which makes me smile or even laugh out loud every time I see one out there.
But, if we're gonna get down to the nitty and gritty and talk technical, I scrutinize them about what they're trying to prove. What is running? How much of it is custom integration and coordination code? Which information crosses the boundary? Which interactions actually work? Where does the AI contribute?
An overlay, an event bridge and a hybrid game can all be worthwhile achievements. Describing them accurately gives the people building them credit for the work they actually did, and gives everyone else a better understanding of what remains unsolved.
Reverse engineering exposes capabilities. Integration connects them. Orchestration gives them new meaning.
Whatever the path you take, ultimately it comes down to our final lesson number six: AI or no AI, REA or whatever comes next...game mashups are a project like any other and still take a lot of work!
As for whether solving Candy Crush puzzles before reloading a gun in Call of Duty is a good idea...that is up for debate!
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<a id="appendix-a-real-world-example"></a>
Appendix: A real-world example
The Universal Modder repository documents a Minecraft and GTA V story-mode example. Its description identifies a Minecraft Fabric mod, a ScriptHookV component and a ReShade add-on, with camera, ground and event information exchanged over a local WebSocket connection. It also describes combining Minecraft’s colour and depth output with GTA’s frame, and translating selected Minecraft events into GTA effects.[1]
There are two useful ideas in that description.
First, the games have specific integration components. A communication channel carries information, but code still has to decide what to send and what the receiving game should do with it.
Second, presentation and interaction are separate problems. Depth information helps decide which rendered surfaces should appear in front of others. That can make the combined image convincing. Making an object affect the other game’s simulation requires additional behaviour.
That is a substantial achievement. It is also a much more precise claim than “any two games can now be merged.” The project’s documented approach is evidence about that example, not a universal explanation for every viral mashup.
---
Sources
Project documentation checked on 20 October 2026; collision reference added on 29 October 2026. Named implementations are described from their maintainers’ documentation; I have not independently run or benchmarked them.
1. Universal Modder: documented Minecraft × GTA V example.
2. REA: overview and how it works.
3. Mod Engine 2: runtime patching, launcher and extension documentation.
4. Godot documentation: collision shapes, physics bodies and collision response. General collision concepts; not evidence of a particular Halo mod implementation.
Conheça universal-modder — inteligência artificial open source em alta no GitHub
Point Claude at any game. Skills, tools and the fal MCP that let Claude Code mod almost any PC game you own: r. Repositório oficial: rehan-remade/universal-modder (Python, licença MIT, 0 estrelas). #universalmodder #rehanremade #python #opensource #github #ai #programacao #tecnologia #ia #devbr #shorts #dicadehoje
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universal-modder packages skills, a CLI and the fal MCP server so an agent can recon, reverse-engineer and mod a PC game, then leave a field note for the next agent. How the loop works: rehan-remade/universal-modder
#GameModding #AIAgents #MCP
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universal-modder gives coding agents a ten-step loop for modding games, and a notebook they write for each other
The idea I would keep from universal-modder is not any single mod. It is the knowledge/ folder, which the README calls a knowledge base that AIs write for AIs. Every agent that finishes a mod can open a pull request with a field note, so the next agent starts where it left off instead of rediscovering the same traps. The skills and tools are how an agent mods a game. The field notes are meant to save the next agent from rediscovering the same problems.
universal-modder is a set of skills, tools and a shared knowledge base that let an AI coding agent mod almost any PC game you own. Per the README, the agent finds the game, works out the engine and the route, reads the real code, builds the mod, makes art, 3D and sound with fal, tests it in the running game, cuts a video, and writes down what it learned. It is MIT licensed.
The same ten-step loop every time
The agent starts with a skill called mod-any-game and, according to the README, runs the same loop for every request:
1. search the knowledge base;
2. recon, then pick a route;
3. set up a safe lab, with saves backed up;
4. read the actual code;
5. build one working slice;
6. generate assets;
7. verify in the real game;
8. record;
9. package;
10. write a field note for the next agent.
Step three and step five are the ones I would point to if someone asked whether this is responsible. Backing up saves before touching anything, and building one working slice before expanding, are the habits a careful human modder has. The skill writes both habits into the workflow itself.
The README's example prompts range from a homing missile launcher in Terraria to a new Age of Empires II civilization with a unit rendered from 3D, and to a question as simple as "What engine is C:\Games\Foo, and has anyone modded it before?"
What a field note contains
Each note in knowledge/ records how a specific game was actually modded, decompiled or reverse-engineered: the exact versions that worked, the route and why, what the engine really does, how it was verified, and the gotchas written as symptom, cause and fix. The um CLI handles the workflow, with um kb search for prior art, um kb new to start a note, um kb check to validate it, and um kb pr to branch, push and open the pull request.
The comment beside that last command says to run it "after your human says OK". The contribution rules in CONTRIBUTING.md, which the README says apply to humans and AIs, are: no game files, no decompiled dumps, no cheating other players, and an honest status and verification.
The skill set
The README lists a dozen skills. game-recon covers prior notes, engine and version, anti-cheat, loaders and save folders, and writes a MODDING_PLAN.md. reverse-engineering drives ILSpy, Cpp2IL, Vineflower, Ghidra and IDA over MCP, Cheat Engine, Frida and RenderDoc, and asks the agent to prove a reverse-engineered file format with a round trip. fal-assets and asset-pipeline turn generated art into engine-exact frames. game-automation launches the game, takes screenshots and clicks safely. Others handle showcase video, game-in-a-game mashups, publishing and porting an existing mod to a newer version.
The engine playbooks inside mod-any-game name Unity, Unreal, .NET and XNA games such as Terraria and Stardew, Godot, Source, Bethesda, Minecraft and several more engine families.
Setup and costs
The install table covers Claude Code, Codex, Gemini CLI, VS Code with Copilot, Cursor and OpenCode, plus a skills-only path through npx skills add for any agent. Each gets the same skills, the fal MCP server and the um CLI. You also need Git, Python 3.10 or newer and ffmpeg, and Blender for 3D-to-sprite renders.
Using fal for assets needs a fal API key or fal's browser sign-in. The README recommends storing it with um fal key set, which puts it in the Linux desktop keyring or an owner-only file elsewhere, rather than in a shell profile or .env. Without a key, fal's OAuth relay signs you in through the browser, and um comfy can make images on a local ComfyUI server. The um sprixen command uses a separate paid service with its own API key.
If you want to try it, start with the recon question about a game you already own, read the MODDING_PLAN.md it produces, and only then let it build.
---
GitHub: rehan-remade/universal-modder
---
Curated by Agent Palisade — practical AI for small and mid-sized businesses.
Revolutionize Your Gaming: AI Just Made Modding *Any* PC Game a Reality!
---
title: Revolutionize Your Gaming: AI Just Made Modding Any PC Game a Reality!
published: True
tags: ai, game, developer, gaming
---
Quick Summary: 📝
Universal Modder is a Python-based framework that enables AI coding agents to automatically generate mods for PC games. It provides skills and tools for game recon, reverse engineering, asset creation (art, 3D, audio), in-game testing, and video generation, fostering a community for sharing and remixing mods.
Key Takeaways: 💡
- ✅ "universal-modder" enables AI coding agents to mod almost any PC game.
- ✅ It automates game engine analysis, code modification, asset creation (art, 3D, sound), and in-game testing.
- ✅ The project significantly lowers the barrier to entry for game modding, empowering developers and gamers alike.
- ✅ AI agents learn from each mod, building a shared knowledge base for continuous improvement and new capabilities.
- ✅ An upcoming mod hub will facilitate sharing, remixing, and community collaboration around AI-generated mods.
Project Statistics: 📊
- ⭐ Stars: 8753
- 🍴 Forks: 961
- ❗ Open Issues: 2
Tech Stack: 💻
- ✅ Python
Hey fellow developers and gaming enthusiasts! Ever dreamed of tweaking your favorite PC games, adding new features, or just seeing what wild ideas you could bring to life, but felt intimidated by complex game engines or obscure modding tools? What if I told you that the future of game modding is here, and it's powered by AI? Get ready to have your mind blown by a truly groundbreaking GitHub project called "universal-modder." This isn't just another tool; it's a game-changer that lets any AI coding agent mod almost any PC game you own! This project is set to democratize game modding in a way we've only dreamed of.
So, how does this magic happen? "universal-modder" is essentially a comprehensive toolkit that empowers AI agents to become expert game modders. Imagine pointing your favorite AI assistant – be it Claude Code, GitHub Copilot, Gemini CLI, or others – at a game on your PC. This project equips the AI with the skills to find the game, figure out what engine it's running on, read the actual game's code, and then intelligently build a mod. But it doesn't stop there! The AI can even generate custom art, 3D models, and sounds using services like fal.ai, seamlessly integrate them into the game, and then test the mod directly within the running game environment. It's like having a super-smart, tireless modding assistant at your beck and call, capable of handling everything from code injection to asset creation. Plus, it learns from every mod it creates, building a shared knowledge base for future agents. This means the more it's used, the smarter and more capable it becomes at tackling new modding challenges!
The benefits for us developers are immense. First, it drastically lowers the barrier to entry for game modding. You don't need to be an expert in every obscure game engine or reverse-engineering technique; the AI handles the heavy lifting and complex technicalities. This frees up your creativity, allowing you to focus on the ideas – the fun part – rather than the intricate implementation details. Want to see Minecraft mobs fighting in Los Santos? Or a Halo Warthog cruising through a blocky world? "universal-modder" makes these wild crossovers a tangible reality. It saves countless hours of tedious work, automates asset creation, and even handles the crucial step of in-game testing. Think of the prototypes you could build, the crazy experiments you could run, or the quality-of-life improvements you could whip up for your favorite titles with unprecedented speed and ease. And the best part? A dedicated mod hub at universalmodder.com is coming next, where you can publish your creations, remix others' mods, and collaborate with a growing community. This project truly democratizes game development and modding, making it accessible, incredibly powerful, and genuinely fun. If you've ever dreamt of bending games to your will, this is the tool you absolutely need to explore. Seriously, this project is a paradigm shift. It's not just about making mods; it's about unlocking a new era of creative freedom for gamers and developers alike. Stop dreaming and start modding – your AI assistant is ready to help you transform your gaming world! Go check out "universal-modder" on GitHub today!
Learn More: 🔗
View the Project on GitHub
---
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Conheça universal-modder — inteligência artificial open source em alta no GitHub
Point Claude at any game. Skills, tools and the fal MCP that let Claude Code mod almost any PC game you own: r. Repositório oficial: rehan-remade/universal-modder (Python, licença MIT, 0 estrelas). #universalmodder #rehanremade #python #opensource #github #ai #programacao #tecnologia #ia #devbr #shorts #dicadehoje
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5 Free GitHub Repos That Take Apart Any Software — Ghidra, Diagram Design, Universal Modder & More
Five free, open-source GitHub repos that decompile apps, mod games, draw your diagrams, fix your SwiftUI and stretch your agent's context — how each works, what paid tool it replaces, and where it breaks.
Chapters:
0:00 The five
0:17 #5 billion-context
1:06 #4 SwiftUI Agent Skill
1:55 #3 Universal Modder
2:42 #2 Diagram Design
3:29 #1 Ghidra
4:16 The ranking
Repos:
Ghidra - NationalSecurityAgency/ghidra
Diagram Design - cathrynlavery/diagram-design
Universal Modder - rehan-remade/universal-modder
SwiftUI Agent Skill - twostraws/SwiftUI-Agent-Skill
billion-context - ranxianglei/billion-context
New free, open-source tools every few days - subscribe.
#github #opensource #ai
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🔗 rehan-remade/universal-modder
Which game would you mod first?
#AI #Gaming #OpenSource #AIAgents
1 like
Modding PC split-screen games (RE6, CoD) for custom couch co-op modes: what open-source tools to use? Universal Modder?
Hi guys,
I'm looking into modding PC split-screen games (e.g., Resident Evil 6, Call of Duty, etc.) to create custom local co-op experiences for me and a friend.
Specifically, I'd love to script custom mini-games featuring:
- Waves of enemies (survival style)
- Custom gameplay rules
- Randomized loot drops
Does a universal framework exist for this kind of scripting, or does it strictly depend on each game's engine?
I found this Universal Modder repoon GitHub—is that my only option, or are there other open-source tools you'd recommend?
1 point
Mentions
Point your AI agent at almost any PC game you own and watch it reverse engineer, mod, test and film the result. 🔗 rehan-remade/universal-modder Credits: rehan-remade/universal-modder #universalmodder #python #gamemodding
AI Game Mashups: Can AI Really Turn Two Games Into One? Mario shooting some baddies in Halo. Minecraft inside GTA V ([see Appendix: a real-world example](#appendix-a-real-world-example)). A social media trend has people sharing videos of what’s being branded as “AI game mashups.” The claim is that people have used AI to reverse engineer different games and mash them together into one in unexpected or cool ways... but is that the whole story? As usual, hype has a tendency to exaggerate things to create, well, more hype. So let's separate reality from fiction and explore what’s actually happening behind these demos. The good news is that there is plenty on the reality side to be mind-blown about! However, there are also some disappointing truths. At least for the time being. Let's Mash Candy Crush And Call of Duty! Let's walk through a ridiculous combination as a practical example. Let's imagine that we want to combine Candy Crush and Call of Duty! However, simply naming two games does not constitute a plan. Like anything else, first we need to work out our requirements and architectural concerns. Here's my take: every time you reload your weapon, Candy Crush loads inside the Call of Duty gameplay and you have to complete a match-three puzzle before the reload can finish. !Concept illustration of a match-three puzzle overlay interrupting a first-person shooter reload. Hypothetical mashup: solve a match-three puzzle to finish reloading. AI-generated concept illustration, not a screenshot of a working mod. I have no idea whether that would be fun. I suspect my teammates would have opinions. But at least we now have something concrete enough to discuss. There are still decisions to make though. Does the shooter pause while you solve the puzzle? What happens if you fail? Can you cancel? Does a harder puzzle earn you more ammunition? Neither original game contains the answers so it's up to us to introduce new rules. And that is our first lesson: Connecting two game engines does not automatically create coherent new gameplay. Somebody, potentially with AI assistance, still has to decide what the connection means and implement it. What Are We Actually Mashing Together? When I watch these demos, I find it useful to separate four things. | What’s happening | What it establishes | | --- | --- | | Visual composition | Images or rendered objects from different sources appear together. | | Event integration | Something happening in one game triggers something in another. | | Gameplay orchestration | New rules coordinate actions and state across the games. | | Hybrid game design | Those rules form a coherent experience with its own objectives, constraints and balance. | These can overlap. A project might combine graphics and translate a few events without sharing every part of either simulation. For example, an explosion in one game could trigger an explosion in another. That is a meaningful integration, but it doesn’t, by itself, establish that every object in both worlds can collide, that both physics engines agree, or that every mission works across the boundary. A clip can still demonstrate a specific interaction beautifully while leaving those broader questions unanswered. The missing interfaces Ok, so how can we go about implementing our Call of Duty and Candy Crush mash-up? Well, to begin with we need to discover each game's available integration points. Then we need to find a way to connect those before finally figuring out how to coordinate the result. 1. Find a way to control the relevant behaviour A game with a supported modding API might already expose the events and controls we need. Otherwise, investigating its internal behaviour may be necessary. For our shooter, we would need to identify a reload request and find a reliable way to defer it. For the puzzle, we need to start a challenge and detect its completion. Observing an animation on screen is different from having a dependable signal that the underlying action succeeded. This is where reverse engineering can contribute: working out how software behaves when its original source code or a suitable interface isn’t available. REA, or Reverse Engineer Anything, is one project in this area and the one behind the viral game mashups trend. Its documentation describes connecting agents to analysis tools, including Ghidra, Hopper and IDA, and returning findings that an agent can investigate further. It is indeed a pretty cool tool that gives an agent ways to inspect software. However, it is NOT a magical command that enables agents to recover an entire game’s original source project or to understand every subsystem. Moreover, it's important to remember that runtime modification of games predates AI tools. Mod Engine 2, for example, documents runtime patching and injection for Souls games, including Elden Ring.[3] Existing tools and community knowledge are part of the foundation here. 2. Build interfaces between the games Once we understand the relevant behaviour, we can build adapters: code that translates between what our mashup needs and what each game can actually do. From the coordinating code’s perspective, the shooter adapter might offer operations such as “defer reload” or “resume gameplay.” The puzzle adapter might offer “start challenge” and a completion event. Those are interfaces that we have to build unless the game itself provides out-of-the-box integration points, or in simpler language, hooks. This could be, for example, official support for mods. That means creating and maintaining your own adapter code, which, yes, you can also use AI to help you generate. There is an added complication: If components run in separate processes, they need a way to exchange messages, such as sockets or named pipes. This is referred to as inter-process communication, often shortened to IPC. A hook and a communication channel have different jobs. A hook can intercept behaviour inside a game whereas IPC lets separate processes exchange information. Having one doesn’t automatically give us the other. Either way, we arrive at our second lesson: AI doesn't somehow make two incompatible executables magically understand each other. The real magic is that AI can help us build the missing interfaces between them. 3. Implement the new rules Now we need the coordinator, or orchestrator, that implements our reload rule so we can load Candy Crush every time you need to reload your weapon on Call of Duty. Here's the plan: it receives a reload request, defers the action, puts the shooter into an appropriate paused state, and opens the puzzle. On success, it allows the reload to proceed and returns control to the shooter. !Flow diagram showing the reload request, deferred reload, paused shooter, puzzle outcome, and success or recovery paths. The orchestrator coordinates the reload and puzzle, with a recovery path for failure, cancellation or timeout. This conceptual flow assumes the required integration points exist. What if the puzzle crashes though? The player shouldn’t remain trapped forever with a frozen gun. And how about if a completion message arrives twice? We need to be careful not to grant ammunition twice. Like any piece of software we need to design for our error conditions. This is why “pause the game” deserves scrutiny. Preventing player input is different from pausing the simulation. In a networked game, the server and other players may continue regardless. Our example depends on capabilities that may be unavailable or prohibited in a protected online title. If you work with microservices, there’s a familiar architectural idea here. Connecting two services doesn’t automatically create an e-commerce application. You still need rules that define what placing an order means, what happens next, and how failure is handled. Games add another difficulty, one that becomes our third lesson: we still need to design and build gameplay rules for the mashup much like building any other game. Do the games become one program? They don’t have to. In one possible implementation of our example, the shooter and puzzle remain separate processes while our own coordinator manages their behaviour and presentation. The simplest implementation may be, for example, switching back and forth between the Candy Crush puzzle’s window and the Call of Duty window. A more integrated version could display the puzzle within the shooter’s view as ensioned in our concept above. We'll have to work harder for it because it then adds rendering and input-routing work but it does look super cool. Either way, the objective is to have the player experience a single set of rules while multiple programs do the work. Another consideration is whether we need to create our own launcher app. This could gives even more control over the runtime and coordination between the two processes running either game, however it does not automatically give control over either game's internals. So lesson four is: the desired user experience dictates how much control you need to have over either game and determines the architectural choices as well as the amount of code that you need to write and maintain. Where did the graphics come from? This is perhaps the most intriguing question. A newly written game might use original artwork, generated assets, placeholders or reused material. A mod might leave the original game’s engine and assets in place. A mashup might combine output from two running engines, each rendering its own content. Those are different workflows. A familiar character on screen doesn’t tell you which one happened. In our hypothetical example, if both original games were running, neither would need its graphics recreated merely to appear in the experience. Each game already knows how to render its own world. The integration challenge would concern control, communication, presentation and the new rules. Conversely, reproducing familiar graphics in a newly written program doesn’t establish that the original physics, enemy behaviour, timing or levels have been reproduced. But hang on. If we put Mario inside Halo, how does he know where the floor is? Doesn’t he come with his own bounding box? The important distinction is that a character’s appearance and its collision behaviour are separate things. A visible model doesn’t automatically bring a working physics system with it. For a hypothetical model replacement, we could give an existing Halo character Mario’s appearance while keeping the host character’s movement and collision setup. Or, if we were adding a new character, we would need to create or convert the collision data into a form the host engine understands and configure its behaviour. Halo wouldn’t need to recognise “Mario”; it would need a correctly configured character in its own simulation. That could stop him falling through the floor without reproducing how he moves in a Mario game. So lesson number five is: Looking like two worlds have merged does not mean that their physics have merged too. There's work to be done to make that happen. Asset provenance and permission are also separate questions from whether an integration works. A clip alone cannot answer them. Before making claims about how a creator obtained the assets, we need their documentation. Where does the AI fit? We should distinguish AI helping build the mashup from AI running it. During development, an agent can use tools to investigate behaviour, propose integration code and help iterate on failures. REA’s documented workflow, for example, lets an agent inspect findings, ask follow-up questions, and write and test an implementation.[2] But once our reload rule works, it can run as ordinary deterministic code. Receive the event, start the puzzle, wait for a result, update the state. There is no inherent need to ask a language model what should happen every time the player reloads. AI can be the engineer that builds the bridge without being the driver that crosses it. That distinction also helps us evaluate claims about speed. A successful demo shows that someone achieved a result. Understanding how much AI accelerated it requires more evidence: the starting tools, existing mods, development history, human interventions and failed attempts. The finished clip doesn’t contain that history. Appreciate the demo. Be precise about the claim. I find this trend exciting because it opens up questions about what people might build when investigating and connecting unfamiliar software becomes more accessible. Not to mention that level of creativity which makes me smile or even laugh out loud every time I see one out there. But, if we're gonna get down to the nitty and gritty and talk technical, I scrutinize them about what they're trying to prove. What is running? How much of it is custom integration and coordination code? Which information crosses the boundary? Which interactions actually work? Where does the AI contribute? An overlay, an event bridge and a hybrid game can all be worthwhile achievements. Describing them accurately gives the people building them credit for the work they actually did, and gives everyone else a better understanding of what remains unsolved. Reverse engineering exposes capabilities. Integration connects them. Orchestration gives them new meaning. Whatever the path you take, ultimately it comes down to our final lesson number six: AI or no AI, REA or whatever comes next...game mashups are a project like any other and still take a lot of work! As for whether solving Candy Crush puzzles before reloading a gun in Call of Duty is a good idea...that is up for debate! --- <a id="appendix-a-real-world-example"></a> Appendix: A real-world example The Universal Modder repository documents a Minecraft and GTA V story-mode example. Its description identifies a Minecraft Fabric mod, a ScriptHookV component and a ReShade add-on, with camera, ground and event information exchanged over a local WebSocket connection. It also describes combining Minecraft’s colour and depth output with GTA’s frame, and translating selected Minecraft events into GTA effects.[1] There are two useful ideas in that description. First, the games have specific integration components. A communication channel carries information, but code still has to decide what to send and what the receiving game should do with it. Second, presentation and interaction are separate problems. Depth information helps decide which rendered surfaces should appear in front of others. That can make the combined image convincing. Making an object affect the other game’s simulation requires additional behaviour. That is a substantial achievement. It is also a much more precise claim than “any two games can now be merged.” The project’s documented approach is evidence about that example, not a universal explanation for every viral mashup. --- Sources Project documentation checked on 20 October 2026; collision reference added on 29 October 2026. Named implementations are described from their maintainers’ documentation; I have not independently run or benchmarked them. 1. Universal Modder: documented Minecraft × GTA V example. 2. REA: overview and how it works. 3. Mod Engine 2: runtime patching, launcher and extension documentation. 4. Godot documentation: collision shapes, physics bodies and collision response. General collision concepts; not evidence of a particular Halo mod implementation.
Conheça universal-modder — inteligência artificial open source em alta no GitHub Point Claude at any game. Skills, tools and the fal MCP that let Claude Code mod almost any PC game you own: r. Repositório oficial: rehan-remade/universal-modder (Python, licença MIT, 0 estrelas). #universalmodder #rehanremade #python #opensource #github #ai #programacao #tecnologia #ia #devbr #shorts #dicadehoje
universal-modder packages skills, a CLI and the fal MCP server so an agent can recon, reverse-engineer and mod a PC game, then leave a field note for the next agent. How the loop works: rehan-remade/universal-modder #GameModding #AIAgents #MCP
universal-modder gives coding agents a ten-step loop for modding games, and a notebook they write for each other The idea I would keep from universal-modder is not any single mod. It is the knowledge/ folder, which the README calls a knowledge base that AIs write for AIs. Every agent that finishes a mod can open a pull request with a field note, so the next agent starts where it left off instead of rediscovering the same traps. The skills and tools are how an agent mods a game. The field notes are meant to save the next agent from rediscovering the same problems. universal-modder is a set of skills, tools and a shared knowledge base that let an AI coding agent mod almost any PC game you own. Per the README, the agent finds the game, works out the engine and the route, reads the real code, builds the mod, makes art, 3D and sound with fal, tests it in the running game, cuts a video, and writes down what it learned. It is MIT licensed. The same ten-step loop every time The agent starts with a skill called mod-any-game and, according to the README, runs the same loop for every request: 1. search the knowledge base; 2. recon, then pick a route; 3. set up a safe lab, with saves backed up; 4. read the actual code; 5. build one working slice; 6. generate assets; 7. verify in the real game; 8. record; 9. package; 10. write a field note for the next agent. Step three and step five are the ones I would point to if someone asked whether this is responsible. Backing up saves before touching anything, and building one working slice before expanding, are the habits a careful human modder has. The skill writes both habits into the workflow itself. The README's example prompts range from a homing missile launcher in Terraria to a new Age of Empires II civilization with a unit rendered from 3D, and to a question as simple as "What engine is C:\Games\Foo, and has anyone modded it before?" What a field note contains Each note in knowledge/ records how a specific game was actually modded, decompiled or reverse-engineered: the exact versions that worked, the route and why, what the engine really does, how it was verified, and the gotchas written as symptom, cause and fix. The um CLI handles the workflow, with um kb search for prior art, um kb new to start a note, um kb check to validate it, and um kb pr to branch, push and open the pull request. The comment beside that last command says to run it "after your human says OK". The contribution rules in CONTRIBUTING.md, which the README says apply to humans and AIs, are: no game files, no decompiled dumps, no cheating other players, and an honest status and verification. The skill set The README lists a dozen skills. game-recon covers prior notes, engine and version, anti-cheat, loaders and save folders, and writes a MODDING_PLAN.md. reverse-engineering drives ILSpy, Cpp2IL, Vineflower, Ghidra and IDA over MCP, Cheat Engine, Frida and RenderDoc, and asks the agent to prove a reverse-engineered file format with a round trip. fal-assets and asset-pipeline turn generated art into engine-exact frames. game-automation launches the game, takes screenshots and clicks safely. Others handle showcase video, game-in-a-game mashups, publishing and porting an existing mod to a newer version. The engine playbooks inside mod-any-game name Unity, Unreal, .NET and XNA games such as Terraria and Stardew, Godot, Source, Bethesda, Minecraft and several more engine families. Setup and costs The install table covers Claude Code, Codex, Gemini CLI, VS Code with Copilot, Cursor and OpenCode, plus a skills-only path through npx skills add for any agent. Each gets the same skills, the fal MCP server and the um CLI. You also need Git, Python 3.10 or newer and ffmpeg, and Blender for 3D-to-sprite renders. Using fal for assets needs a fal API key or fal's browser sign-in. The README recommends storing it with um fal key set, which puts it in the Linux desktop keyring or an owner-only file elsewhere, rather than in a shell profile or .env. Without a key, fal's OAuth relay signs you in through the browser, and um comfy can make images on a local ComfyUI server. The um sprixen command uses a separate paid service with its own API key. If you want to try it, start with the recon question about a game you already own, read the MODDING_PLAN.md it produces, and only then let it build. --- GitHub: rehan-remade/universal-modder --- Curated by Agent Palisade — practical AI for small and mid-sized businesses.
Revolutionize Your Gaming: AI Just Made Modding *Any* PC Game a Reality! --- title: Revolutionize Your Gaming: AI Just Made Modding Any PC Game a Reality! published: True tags: ai, game, developer, gaming --- Quick Summary: 📝 Universal Modder is a Python-based framework that enables AI coding agents to automatically generate mods for PC games. It provides skills and tools for game recon, reverse engineering, asset creation (art, 3D, audio), in-game testing, and video generation, fostering a community for sharing and remixing mods. Key Takeaways: 💡 - ✅ "universal-modder" enables AI coding agents to mod almost any PC game. - ✅ It automates game engine analysis, code modification, asset creation (art, 3D, sound), and in-game testing. - ✅ The project significantly lowers the barrier to entry for game modding, empowering developers and gamers alike. - ✅ AI agents learn from each mod, building a shared knowledge base for continuous improvement and new capabilities. - ✅ An upcoming mod hub will facilitate sharing, remixing, and community collaboration around AI-generated mods. Project Statistics: 📊 - ⭐ Stars: 8753 - 🍴 Forks: 961 - ❗ Open Issues: 2 Tech Stack: 💻 - ✅ Python Hey fellow developers and gaming enthusiasts! Ever dreamed of tweaking your favorite PC games, adding new features, or just seeing what wild ideas you could bring to life, but felt intimidated by complex game engines or obscure modding tools? What if I told you that the future of game modding is here, and it's powered by AI? Get ready to have your mind blown by a truly groundbreaking GitHub project called "universal-modder." This isn't just another tool; it's a game-changer that lets any AI coding agent mod almost any PC game you own! This project is set to democratize game modding in a way we've only dreamed of. So, how does this magic happen? "universal-modder" is essentially a comprehensive toolkit that empowers AI agents to become expert game modders. Imagine pointing your favorite AI assistant – be it Claude Code, GitHub Copilot, Gemini CLI, or others – at a game on your PC. This project equips the AI with the skills to find the game, figure out what engine it's running on, read the actual game's code, and then intelligently build a mod. But it doesn't stop there! The AI can even generate custom art, 3D models, and sounds using services like fal.ai, seamlessly integrate them into the game, and then test the mod directly within the running game environment. It's like having a super-smart, tireless modding assistant at your beck and call, capable of handling everything from code injection to asset creation. Plus, it learns from every mod it creates, building a shared knowledge base for future agents. This means the more it's used, the smarter and more capable it becomes at tackling new modding challenges! The benefits for us developers are immense. First, it drastically lowers the barrier to entry for game modding. You don't need to be an expert in every obscure game engine or reverse-engineering technique; the AI handles the heavy lifting and complex technicalities. This frees up your creativity, allowing you to focus on the ideas – the fun part – rather than the intricate implementation details. Want to see Minecraft mobs fighting in Los Santos? Or a Halo Warthog cruising through a blocky world? "universal-modder" makes these wild crossovers a tangible reality. It saves countless hours of tedious work, automates asset creation, and even handles the crucial step of in-game testing. Think of the prototypes you could build, the crazy experiments you could run, or the quality-of-life improvements you could whip up for your favorite titles with unprecedented speed and ease. And the best part? A dedicated mod hub at universalmodder.com is coming next, where you can publish your creations, remix others' mods, and collaborate with a growing community. This project truly democratizes game development and modding, making it accessible, incredibly powerful, and genuinely fun. If you've ever dreamt of bending games to your will, this is the tool you absolutely need to explore. Seriously, this project is a paradigm shift. It's not just about making mods; it's about unlocking a new era of creative freedom for gamers and developers alike. Stop dreaming and start modding – your AI assistant is ready to help you transform your gaming world! Go check out "universal-modder" on GitHub today! Learn More: 🔗 View the Project on GitHub --- 🌟 Stay Connected with GitHub Open Source! > 📱 Join us on Telegram > Get daily updates on the best open-source projects > GitHub Open Source > 👥 Follow us on Facebook > Connect with our community and never miss a discovery > GitHub Open Source
Conheça universal-modder — inteligência artificial open source em alta no GitHub Point Claude at any game. Skills, tools and the fal MCP that let Claude Code mod almost any PC game you own: r. Repositório oficial: rehan-remade/universal-modder (Python, licença MIT, 0 estrelas). #universalmodder #rehanremade #python #opensource #github #ai #programacao #tecnologia #ia #devbr #shorts #dicadehoje
5 Free GitHub Repos That Take Apart Any Software — Ghidra, Diagram Design, Universal Modder & More Five free, open-source GitHub repos that decompile apps, mod games, draw your diagrams, fix your SwiftUI and stretch your agent's context — how each works, what paid tool it replaces, and where it breaks. Chapters: 0:00 The five 0:17 #5 billion-context 1:06 #4 SwiftUI Agent Skill 1:55 #3 Universal Modder 2:42 #2 Diagram Design 3:29 #1 Ghidra 4:16 The ranking Repos: Ghidra - NationalSecurityAgency/ghidra Diagram Design - cathrynlavery/diagram-design Universal Modder - rehan-remade/universal-modder SwiftUI Agent Skill - twostraws/SwiftUI-Agent-Skill billion-context - ranxianglei/billion-context New free, open-source tools every few days - subscribe. #github #opensource #ai
🔗 rehan-remade/universal-modder Which game would you mod first? #AI #Gaming #OpenSource #AIAgents
Modding PC split-screen games (RE6, CoD) for custom couch co-op modes: what open-source tools to use? Universal Modder? Hi guys, I'm looking into modding PC split-screen games (e.g., Resident Evil 6, Call of Duty, etc.) to create custom local co-op experiences for me and a friend. Specifically, I'd love to script custom mini-games featuring: - Waves of enemies (survival style) - Custom gameplay rules - Randomized loot drops Does a universal framework exist for this kind of scripting, or does it strictly depend on each game's engine? I found this Universal Modder repoon GitHub—is that my only option, or are there other open-source tools you'd recommend?