Cut Token Costs by 90% with RTK: A High‑Performance CLI Proxy for Claude Code
This article introduces RTK, a high‑performance CLI proxy that filters and compresses command output before it reaches Claude Code's 200k LLM context, reducing token consumption by 60‑90% and improving inference speed, with step‑by‑step installation and usage instructions.
RTK Overview
RTK is a high‑performance command‑line proxy designed to filter and compress command output before it enters Claude Code’s 200k token LLM context. By doing so, it can cut token usage by 60‑90%, preserving inference quality while lowering costs.
Installation
Installation steps for Windows are provided.
Download the release package from https://github.com/rtk-ai/rtk/releases.
Extract the archive to obtain rtk.exe and add its directory to the system Path environment variable, e.g., Path = D:\developer\tools\rtk Verify the installation by running rtk --version; a displayed version number confirms success.
Usage with Claude Code
Example commands demonstrate how RTK integrates with Claude Code.
Initialize RTK globally with rtk init -g.
Open Claude Code’s CLAUDE.md configuration file; RTK usage instructions are automatically added.
When executing git status in Claude Code’s CLI, RTK rewrites the command to start with rtk, dramatically reducing the token count sent to the LLM.
RTK supports conversion for over 30 common commands, each achieving significant token savings as illustrated in the accompanying charts.
To view accumulated token savings, run rtk gain.
Conclusion
RTK enhances Claude Code by delivering better reasoning, longer sessions, and lower operational costs. Users interested in more efficient LLM interactions are encouraged to try the tool.
Project URL
https://github.com/rtk-ai/rtkmacrozheng
Dedicated to Java tech sharing and dissecting top open-source projects. Topics include Spring Boot, Spring Cloud, Docker, Kubernetes and more. Author’s GitHub project “mall” has 50K+ stars.
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