srijanshukla18

I've got a skill repository on github, and I got a hermes automation to sync skills repo - this hermes automation is on every device. Any skills I make on the fly - my global AGENTS.md has instructions to update the skills repo path and place them appropriately in there.

Aesthetic fatigue from AI :D I understand, I feel it too.

But yeah I've got zero UI skills - I just wanted to showcase the spin dynamics somehow, so shared it anyway.

Yeah sorry about that. Doesn't look that good on the phone. Try it out once on your laptop/desktop - much better there.

And actually it should all work - just looks cramped on phone.

Got it, I can edit that bit, thanks for the feedback.

Yes! it does do the math for Magnus effect. Source code is all client side you can take a look at it.

But early on when I started this, I prompted the LLMs strongly to focus on having accurate real world physics baked in.

Fair feedback. I've got zero UI skills - I just did put up whatever Fable gave out. That's true.

I put tons of time explaining spin physics to Fable - that was some effort on my part and that's it.

the UI feedback, I'll pass it Fable when its back :D

And yep it doesn't look good on mobile devices - try it on a desktop screen if you can, much better there.

Yeah no idea but I've seen devices that are able to measure spin in real time.

For sure yeah just scratches the surface for now

About the bounce and the answer: great feedback, thank you! When fable is back I'll incorporate these.

But no did not take just 5 minutes :D I was working on this since early Opus days and the output was consistently absolutely horrible. Fable was the first model to produce something okay - then I prompted it for hours explaining exactly what I want to demonstrate and had to even tell it explicitly a lot about how spin works - from my experience

Hey HN, I built Spin Lab: a browser-based interactive explainer for table-tennis spin.

It visualizes topspin/backspin, spin rate, ball trajectory, bounce behavior, and why the opponent’s return reacts the way it does.

I built it because spin is central to table tennis, but most explanations are either too hand-wavy or too static. I wanted something you can scrub, slow down, and experiment with.

This is not a serious benchmark, come on.

Tomorrow I'm launching a benchmark where I check if an LLM can build a Airbus A320 from scratch without internet. (Spoiler: no LLM succeeds)