HN user
Ok, so this is something I also want to do someday. It's not what Squib is at all, but I feel like we need better tools board game simulation and machine learning. In particular, I'd like to simulate the game with very basic AI, then analyze the games to look for overpowered moves (e.g. if 75% of all winners used Black Lotus).
I'm trying to do this in an ad hoc way on my own games, but progress is slow :(
I'm really excited about Paperize. I can't wait to see more of what you're up to.
I simply made a thing that I wanted to use. And then made it open source in case anyone else wanted to contribute. I've used a ton of tools for this task for nearly 10 years now - most notably nanDeck, but trying out just about everything else. I kept saying, "this is cool, but I want to do it in Ruby".
I also wanted an open source alternative to nanDeck. I love nanDeck, and Andrea Nini has been amazingly responsive at fixing bugs quickly, and at pushing out new features frequently. But open source projects (if done right) build more of the user-developer community that I'm looking for.
Regarding being complicated. Personally, I made Squib to match the way I think. Doing rapid prototyping on card games is both complicated tedious no matter which way you slice it. Squib helps with the tedious part. Ruby provides so much to take complex tasks and condense them to readable code - I wanted to leverage that for a very specific task.
Yes, I know some people are scared away by the fact that it's programming. Or the fact that it's Ruby with some native dependencies. But (and this I know from my day job as a software engineering professor) Ruby is among the easiest programming languages to learn. Already, I've seen some folks over at BoardGameGeek enthusiastically pick up Ruby and learn it just for Squib (http://www.boardgamegeek.com/article/19640981). That's awesome and already more than I had hoped for.