Stevengonsalvez

rtk and Headroom are two command-line tools designed to reduce the number of tokens consumed when processing developer tool output for AI agents. rtk operates as a Rust-based CLI proxy that filters and trims the output of development commands at the shell level, significantly reducing the volume of data—such as outputs from ls, grep, git, and test commands—before it reaches the context window used by AI models. The evidence cites reductions of 60-90% in output size for common commands, with examples like a cargo test run generating 25,000 tokens and git status producing 2,000 tokens, much of which may be unnecessary for the agent's task. Headroom complements rtk by acting as a local compression proxy. It compresses tool output, logs, files, and retrieval-augmented generation (RAG) chunks as the data is transmitted, further reducing token usage on the wire. Headroom also includes a feature called CacheAligner, which is intended to protect the prompt cache during this process. These tools are described as stackable, allowing both shell-level trimming and wire-level compression to be applied together for greater token savings. Both tools are positioned as part of a broader "Token Saving stack" and are aimed at optimizing the cost and efficiency of AI agent workflows by minimizing the amount of irrelevant or redundant information processed and sent to language models. The tools are delivered as command-line utilities, with rtk available as a single Rust binary. Pricing information is limited to the mention of "Free Token Saving," suggesting that the tools are available for free, but no further licensing or open-source details are provided. The intended users are developers or those working with AI coding agents who need to manage and reduce token consumption from command outputs, logs, or file data sent to language models. No specific integrations or supported platforms beyond the CLI and Rust binary for rtk are mentioned.