<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Token-Optimization on TPOW Lab</title><link>https://tpow-001.netlify.app/tags/token-optimization/</link><description>Recent content in Token-Optimization on TPOW Lab</description><generator>Hugo</generator><language>en</language><copyright>Copyright &amp;copy; 2025-2026 TPOW-001. All Rights Reserved.</copyright><lastBuildDate>Thu, 04 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://tpow-001.netlify.app/tags/token-optimization/index.xml" rel="self" type="application/rss+xml"/><item><title>claude-code-memory-setup 完整教學</title><link>https://tpow-001.netlify.app/post/2026-06-04-claude-code-memory-setup-tutorial/</link><pubDate>Thu, 04 Jun 2026 00:00:00 +0000</pubDate><guid>https://tpow-001.netlify.app/post/2026-06-04-claude-code-memory-setup-tutorial/</guid><description><![CDATA[<h1 id="claude-code-memory-setup-完整教學" data-numberify>claude-code-memory-setup 完整教學<a class="anchor ms-1" href="#claude-code-memory-setup-完整教學"></a></h1>

<h2 id="1-專案定位與價值" data-numberify>1. 專案定位與價值<a class="anchor ms-1" href="#1-專案定位與價值"></a></h2>

<h3 id="這是什麼" data-numberify>這是什麼？<a class="anchor ms-1" href="#這是什麼"></a></h3>
<p><strong>claude-code-memory-setup</strong> 是一套開源設定指南（MIT 授權），教你如何將 Claude Code 從「每次開 session 都失憶」的狀態，改造為具備 <strong>persistent memory（持久記憶）</strong> 和 <strong>codebase awareness（程式碼感知）</strong> 的智慧 agent。</p>]]></description></item><item><title>Headroom 完整教學 — AI Agent Context Compression Layer</title><link>https://tpow-001.netlify.app/post/2026-06-04-headroom-tutorial/</link><pubDate>Thu, 04 Jun 2026 00:00:00 +0000</pubDate><guid>https://tpow-001.netlify.app/post/2026-06-04-headroom-tutorial/</guid><description><![CDATA[<h1 id="headroom-完整教學--ai-agent-context-compression-layer" data-numberify>Headroom 完整教學 — AI Agent Context Compression Layer<a class="anchor ms-1" href="#headroom-完整教學--ai-agent-context-compression-layer"></a></h1>

<h2 id="1-專案定位" data-numberify>1. 專案定位<a class="anchor ms-1" href="#1-專案定位"></a></h2>
<p>Headroom 是一套 AI agent 的 context compression (上下文壓縮) layer (層)，目標是把 LLM 收到的所有輸入——tool output (工具輸出)、log (日誌)、RAG chunk (檢索增強生成區塊)、檔案內容、對話歷史——在送達 LLM provider 之前進行智慧壓縮，達成 60–95% 的 token (語元) 節省，同時維持回答品質不變。</p>]]></description></item><item><title>RTK (Rust Token Killer) 完整教學 — Claude Code / Copilot / Cursor 的 token 殺手</title><link>https://tpow-001.netlify.app/post/2026-05-20-rtk-tutorial/</link><pubDate>Wed, 20 May 2026 00:00:00 +0000</pubDate><guid>https://tpow-001.netlify.app/post/2026-05-20-rtk-tutorial/</guid><description><![CDATA[<h1 id="rtk-rust-token-killer-完整教學" data-numberify>RTK (Rust Token Killer) 完整教學<a class="anchor ms-1" href="#rtk-rust-token-killer-完整教學"></a></h1>
<blockquote>
<p>一句話：在 LLM agent 跑 shell 命令前先過濾、分群、去重、截斷輸出，把 token 消耗砍 60–90%。</p></blockquote>

<h2 id="1-專案定位" data-numberify>1. 專案定位<a class="anchor ms-1" href="#1-專案定位"></a></h2>
<p><strong>RTK (Rust Token Killer; Rust token 殺手)</strong> 是 Rust 寫的 CLI proxy，定位是「AI agent 與 shell 之間的壓縮層」。和其他類似工具比較：</p>]]></description></item></channel></rss>