I built a TXT based tension engine that helps turn difficult questions into small GitHub experiments.

The basic idea is simple.

A lot of hard questions are too big for normal prompting. You ask an LLM something serious, and it gives you a smooth answer that sounds smart, but does not really help you build anything.

So I made this project as a different kind of starting point.

Instead of treating the model like a generic chatbot, I upload one TXT engine pack, boot it, and use it like a structured question engine. The goal is not to magically produce truth. The goal is to take a messy, high stakes question and push it toward something more buildable: a toy model, a small MVP, a prototype, a simulator, a test harness, or a reproducible experiment.

That is why I started thinking about this less as “one more AI prompt” and more as a tension engine that generates cool GitHub project ideas.

How it works, in simple terms:

1. Download the TXT pack from the repo
2. Upload it to a strong LLM (Thinking mode)
3. Type `run`
4. Type `go`
5. Follow the menu and start with a real question you actually care about

You do not need to learn the full theory first. You can treat it like a weird little project generator.

Under the hood, the engine tries to stop the session from drifting like a normal freeform chat. Instead, it pushes the model into a more fixed reasoning structure. It uses a shared tension language and a larger backbone of problem structures, so the conversation becomes less “vibes only” and more “what kind of system is this, where is the pressure, what breaks first, what can actually be tested.”

That matters because some questions should not stay at the level of slogans.

For example, this engine is much more interesting for questions like:

**Can this climate scenario be turned into a toy world or simulation?**

**Where are the weak links in this system, network, or infrastructure stack?**

**Is this AI setup failing because of alignment, oversight, contamination, or something else?**

**Can this social or political situation be modeled as a system moving toward instability?**

**Can this benchmark, dataset, or synthetic pipeline be turned into an audit style experiment?**

Those are the kinds of questions that can become actual repos.

A toy climate scenario repo. A weak link or systemic crash simulator. An AI oversight MVP. A benchmark audit tool. A synthetic contamination checker. A long horizon risk notebook. A decision lab for hard tradeoffs.

That is the fun part for me.

This project does not try to pretend it already solved those problems. It is not a secret answer machine. It is more like a structured pressure chamber for turning difficult questions into clearer experiment directions.

If you want the shortest possible way to try it, the repo already has a very simple path:

**download the TXT, upload it, type run, type go, then bring one serious question.**

You can stay at that level forever if you want.

If you want more control, you can also use it in a more manual way: pick a problem you care about, treat the chat like a dedicated lab, and push the model to map the situation into explicit structures, warning signs, tradeoffs, and next moves.

That is where it starts feeling less like chat and more like project design.

I think that is why this repo belongs here.

It is not just a wrapper. It is not just another prompt collection. It is a TXT based engine for people who like strange but structured project generators.

If you enjoy GitHub projects that sit somewhere between reasoning tool, world model, experiment lab, and idea machine, you might like this one.

And honestly, the imagination ceiling is probably much higher than the first demo layer. Once you realize you can feed it hard questions and ask for buildable outputs instead of polished opinions, it starts opening a lot of doors.

Repo (1.6k)  
  
[https://github.com/onestardao/WFGY/blob/main/TensionUniverse/EventHorizon/README.md](https://github.com/onestardao/WFGY/blob/main/TensionUniverse/EventHorizon/README.md)