[alansaber]

A lot of people want a use case. One I think might be cool is some kind of spatial/represented comparison: let's see how two different models interact with the codebase (for the same problem), what they touched, and what they did. Or the same model, but averaged across 100 runs, so we can see how much variance there really is per task. Something along those lines sounds interesting to me.

[sdesol]

> A lot of people want a use case.

I think the issue is, on the surface this is very much a "watch this non-deterministic actvity" but I can see the value in it. This is self promotional but I am working on a "Brain" (https://github.com/gitsense/pi-brains) for the Pi (https://github.com/earendil-works/pi) coding agent and I can actually see this being quite useful to quickly tell if you did make an agent smarter or not.

There is obviously different ways you can do this, but I can see being able to quickly visualize changes based on additional knowledge/constraints can be quite useful.

[alansaber]

I'd advise you to put a video demo at the top of your repo, similar to OP, to convince or interest me.

[sdesol]

There are some additional things I need to implement first but I do have a hands on repo that you actually try at

https://github.com/gitsense/gsc-rules-demos

One of the rules shows how you can inject information when you know an agent wants to read a certain file. So if you have skills related to a certain file/directory, you can inject the information when you need to.

So using the OPs visualization tool, if you find the agent wandering you could create a new rule to guide the agent and compare it with and with guidance.

[cosmtrek]

Thanks bro, you see the value of this project!