I built a tool that turns repeated file reads into 13-token references. My AI Coding sessions now use 86% fewer tokens on file-heavy tasks based on mathematics and research. [P]

About this article

I got tired of watching Claude Code re-read the same files over and over. A 2,000-token file read 5 times = 10,000 tokens gone. So I built sqz. The key insight: most token waste isn't from verbose content - it's from repetition. sqz keeps a SHA-256 content cache. First read compresses normally. Every subsequent read of the same file returns a 13-token inline reference instead of the full content. The LLM still understands it. Real numbers from my sessions: File read 5x: 10,000 tokens → 1,400 ...