39 karma · joined September 19, 2023
I built something in the same space but took a different approach — less fun, more engineering: Vox (https://github.com/rtk-ai/vox) — local TTS in pure Rust, no API key, no cloud dependency.
So I built RTK. It wraps commands and strips the junk before it reaches your context: rtk git status # instead of git status rtk find "*.rs" . # compact results rtk ls . # token-optimized tree rtk cargo test # just the test results
My rtk gain -q after 15 days of real usage: Total commands: 7,061 Input tokens: 29.3M Output tokens: 4.8M Tokens saved: 24.6M (83.7%)
Biggest surprise was rtk find — directory listings are insanely wasteful. Run rtk discover on your Claude Code session history to see how many tokens you've been wasting — that's what convinced me to actually build this. Rust, MIT licensed. Happy to hear what commands are the worst token offenders for you.
An open-source multi-cloud governance framework powered by a YAML rule engine. We just reached a milestone by adding Database (DB) support.
The goal is to allow developers to audit configuration and compliance directly within DB instances, alongside standard cloud resources (AWS, GCP, Azure, K8s). We’re focusing on keeping the YAML rules as agnostic as possible so the same logic can apply across different environments without rewriting everything. rtk (https://github.com/rtk-ai/rtk)
This is a "scratching my own itch" project born from using Claude-code. While vibe coding, I got frustrated watching the agent spam ls -al or cat repeatedly just to "orient" itself.
It creates two main issues:
The Token Tax: It burns through tokens for info the agent already has.
Context Pollution: The context window fills up with redundant noise.
rtk acts as a CLI wrapper/filter to make LLM interactions more signal-to-noise efficient. It silences or summarizes redundant outputs so the agent only receives the necessary "delta." It’s a simple attempt to keep the context clean and make sessions last longer before the agent loses the plot.Total commands: 41 Input tokens: 6.8K Output tokens: 1.8K Tokens saved: 6.0K (88.2%)
Command Count Saved Avg% rtk git status 11 2.8K 81.2% rtk grep 3 1.5K 31.9% rtk git push 22 1.3K 92.0% rtk ls 5 431 47.1%
see https://medium.com/@contact_52772/malicious-npm-packages-aut... .
For futur we can add a call to an open source api to list the ban packages. Thank you, Patrick