A tool that turns repeated file reads into 13-token references - saves 86% on file-heavy AI session

I got tired of watching Coding sessions 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.