alt Hacker NewsI would like to have deeper comparison with alternatives like rtk, which are already fast and written in rust, also the previous comments mentioned something that has been a know problem with rtk that it sometimes strips the thing that the llm needs (or expects, causing more work to need to happan not less)
Replies
In term of token saving performance, it should be on par with rtk since it is basically the same idea. The major different is rtk bundled hundreds of filter logic and no room for user to adjust without maintaing user owned fork or opening the pull request while lowfat is using opposite architectural approach by removing almost all filter logic in the binary and seperate user filters as a plugin system
Yeah I use rtk and would love to see a comparison.
None of these tools measure how effective they are...
It's a massive red flag to me when you could get decent data to see if your thing actually works, and they don't even attempt to...
Have the LLM use your tool, run it on several of the coding benchmarks. If you're stingy, run it on the ones that don't cost much.
Otherwise, I'm going to assume it doesn't actually work. If it did - Claude, Antigravity, Codex, Pi, or some major player would bundle tools like this into the CLI / harness.
AFAIK, none of the major players do. That's a sign to me these don't work in general.
I've tried building some tools specific to bug fixing. Intelligently feeding context massively helps smaller models. But, what I've found - surprisingly - is that a smaller, much better focused, including a lot of helpful data as well, has almost no impact on larger models compared to what they do by default.
You do save some tokens, though, which is what they're claiming - but not ~99%...