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sqz tool cuts AI token costs by 86% with smart file reference caching

A new tool called sqz has been developed to significantly reduce token consumption in AI sessions by identifying and de-duplicating repeated file reads. The tool employs a content cache that replaces subsequent reads of the same file with a concise 13-token reference, while preserving critical context like error messages. sqz offers broad compatibility, with plugins for IDEs like VS Code and JetBrains, a browser extension supporting major LLMs, and shell hooks, aiming to save users up to 86% on token costs for file-heavy tasks. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Reduces operational costs for AI users by optimizing token usage, potentially enabling more complex tasks within budget.

RANK_REASON This is a new software tool release that integrates with existing AI products.

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COVERAGE [1]

  1. r/cursor TIER_2 · /u/Due_Anything4678 ·

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

    <!-- SC_OFF --><div class="md"><p>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.</p> <p>The key insight: most token waste isn't from verbose content - it's from repetition. sqz ke…