Caveman
Why Choose Caveman?
if your workflow involves dumping massive prompts into an LLM and watching the bill skyrocket, caveman is probs the fix u need. its main thing is cutting down token usage by like 75% but still keeps the code logic intact. great for devs working with claude or cursor who wanna save cash on api costs without dumbing down the output. honestly, if ur tired of context windows filling up mid-task, this is a solid play. what really stands out is how easy it is to set up. one line install and it plugs straight into most editors like windsurf or copilot. u get four grunt levels so u can tweak how chatty the ai gets, plus it handles input compression n terse commits automatically. basically makes the tool feel faster and cheaper without much setup hassle. though, keep in mind this ain't for everything. since it compresses inputs heavily, creative brainstorming sessions might come off too robotic. its best fit is definitely hard-core coding tasks or debugging rather than general chat. still, for open source folks, the 25k stars say a lot about reliability.
Caveman cuts ~75% of Claude's output tokens without losing technical accuracy. One-line install for Claude Code, Cursor, Windsurf, Copilot, and more. Four grunt levels, terse commits, one-line PR reviews, and input compression built in. 24.9K stars.
Caveman Introduction
What is Caveman?
Caveman is an open source dev tool that layers on top of AI coding assistants like Cursor or Claude to cut down token usage. It slashes roughly 75% of the output text w/out losing tech accuracy which is huge if ur trying to save cash on API bills. Installation takes one line and it comes with input compression, four grunt levels, and help writing way shorter commits or PR reviews. Its pretty much made for devs who are done with wading through fluffy AI responses all day.
How to use Caveman?
Getting started is actually staight frowad enough. u just grab the package from their repo and run the install script. since it plugs into things like cursor or claude, u gotta make sure yer env is set right first. dont sweat the config files much, most folks just run the one-liner and hit ground running. Once its active, focus on the grunt levels. theres four tiers so pick what fits ur budjet. lower ones shred tokens hard but output gets terse, higher ones keep accuracy up but eat credits faster. switching between them is easy depending if ur doing quick commit msg or deep code review stuff. it basically makes the ai talk less without breaking the tech stack. Your first real win is seeing those token counts drop while typing prompts. u just write normal stuff and caveman compresses it before hitting send. works great for big context windows where costs add up fast. just keep testing diff levels til u find the sweet spot betwen speed and quality. no need for fancy docs really, trial and error works best here.
Why Choose Caveman?
if your workflow involves dumping massive prompts into an LLM and watching the bill skyrocket, caveman is probs the fix u need. its main thing is cutting down token usage by like 75% but still keeps the code logic intact. great for devs working with claude or cursor who wanna save cash on api costs without dumbing down the output. honestly, if ur tired of context windows filling up mid-task, this is a solid play. what really stands out is how easy it is to set up. one line install and it plugs straight into most editors like windsurf or copilot. u get four grunt levels so u can tweak how chatty the ai gets, plus it handles input compression n terse commits automatically. basically makes the tool feel faster and cheaper without much setup hassle. though, keep in mind this ain't for everything. since it compresses inputs heavily, creative brainstorming sessions might come off too robotic. its best fit is definitely hard-core coding tasks or debugging rather than general chat. still, for open source folks, the 25k stars say a lot about reliability.