Leanmcp/superview.sh：README 來源編輯指南

Leanmcp/superview.sh 的 README 將專案描述為「See your claude code logs in clear details in your dashboard」。本文只整理倉庫可直接核對的內容，不把 star、Fork 或宣傳語當成品質證明。README 在「Want to see what YOUR Claude Code actually sends?」下寫到：Every request. Every file it reads. Every token it burns.。這說明的是專案邊界，不是已完成的生產驗證。

從 README 的「Why Open Source Matters for AI Coding」與相關條目，可以先判斷它是否處理你的實際問題：Vendor lock-in. Your entire workflow becomes dependent on a single company's pricing decisions, uptime, and continued existence.。若需求不同，不應只因專案熱度就採用。本文保留原始專案名、命令與元件名，方便回到一手來源核對。 README 另外列出一項可核對的資訊：No transparency. You don't know what data is being collected, how your code is being processed, or what happens to your proprietary business logic when it's sent to a remote server.。這類原文條目可用來設計試跑步驟，但不能取代實際環境測試。

README 將運作方式分散在「Run any Claude Code task , go here」等段落。可確認的線索包括：The AI coding assistant space is evolving at breakneck speed. New tools launch every week, existing tools ship major updates constantly, and it's nearly impossible to keep up.。本文不把未寫出的架構、效能或安全邊界補成結論；真正的執行鏈仍要配合目錄、設定檔與版本標籤檢查。

第一次安裝應從 README 指出的入口開始。目前可核對的命令是： # Aider , pip install and go pip install aider-chat aider # OpenCode , single binary curl -fsSL https://opencode.ai/install | sh opencode # Cline , install from VS Code marketplace # Search "Cline" in VS Code extensions # Goose , install via pipx pipx install goose-ai goose session start 如果倉庫沒有命令，本文不會自行編造步驟，而是建議先閱讀「The Ultimate Guide to Open-Source AI Coding Assistants」，確認系統依賴、預設埠與首次初始化。

日常使用取決於專案文件。README 的「Quick Start」段落提到：Want to try one right now? Here are the fastest way to get started with the top tools:。設定檔、環境變數、權限與資料目錄只在來源明確時才會記錄；沒有寫出的預設值，應在測試環境驗證並保留回滾副本。 同一部分也提到：No customization. You can't adapt the tool to your specific needs, integrate it with your internal systems, or fix bugs that affect your team.。