Your AI agent is wasting money. Not because of the model. Because of the context. Every tool call, log file, API response, database query, and RAG chunk gets sent to the LLM. Most of it is noise.…

The 10 fastest growing GitHub repos this week: 1. markitdown (+16.4K stars) Python tool for converting files and office documents to Markdown. 2. headroom (+12.0K stars) Compress tool outputs, logs,…

每月 API 账单肉疼?有个开源项目 Headroom,夹在你和模型中间,把要发的上下文先压一道——日志 65K→5K、代码搜索 17K→1.4K,砍掉九成,答案基本不变。📉 ⚠ 官方自测、第三方未复现;有损,按内容省 47–92%;需本地进程,沙箱/serverless 不适用。 #AI #LLM

Headroom optimizes LLM context by compressing tool outputs and logs by up to 95 percent without loss of accuracy. Available as a library or MCP server, it significantly cuts token costs and latency…

代码分析类的需求可以试着使用一下这个，可以减少60%~90%的token使用。 但是非代码分析类的，比如说知识库文本分析，作用不大。

Check out headroom on GitHub. This tool compresses tool outputs and RAG chunks before they reach the LLM. It reduces token usage by 60 to 95 percent without losing accuracy. Essential for anyone…

Trending repository of the day 📈 headroom Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server. Last 24h: 3,530…

They've built this out as a library, a proxy, and an MCP server, offering a few ways to integrate it. Good to have options for different setups, not just a simple module.

這個 AI 工具有點東西 他真的能夠節省滿大量的 token 消耗 但截至目前的使用感想還不錯 提醒 如果是用 Codex APP ，要走本地 MCP 不能通過改base url 的方式 否則多線併發的任務會一直回 bad request 或是 reconnect このAIツール、かなり面白い。…

CN: 你还在把长日志整段喂给 AI？Headroom 今天冲上 GitHub Trending，核心不是换模型，而是先压缩上下文。先试3步：install → wrap codex/claude → perf。 EN: Still pasting huge logs into AI? Headroom says compress first, send later.