SuperClaude v3.0.0.1 是一個革命性的 Claude Code 配置框架，將通用 AI 助手轉變為專業的企業級開發夥伴。該框架通過 16 個專業化命令、9 個認知角色和 70% 的 Token 優化，已為 6,500+ 開發者提供了結構化、高效的 AI 輔助開發解決方案。
從技術架構師的角度分析，SuperClaude 解決了企業級開發中的三大核心挑戰：AI 助手缺乏專業化、開發工作流程標準化困難，以及 Token 成本過高。通過證據驅動的方法論和模塊化設計，它為現代軟體開發提供了可擴展、可維護的 AI 輔助框架。
如果您是從 SuperClaude v2 升級，請注意以下關鍵變化：
SuperClaude/ (舊的專案根目錄)
| package main | |
| import ( | |
| "fmt" | |
| "math/rand" | |
| "runtime" | |
| "strconv" | |
| "sync" | |
| "time" | |
| ) |
Here are the simple steps needed to create a deployment from your lokal GIT repository to a server based on this in-depth tutorial.
You are developing in a working-copy on your local machine, lets say on the master branch. Most of the time, people would push code to a remote server like github.com or gitlab.com and pull or export it to a production server. Or you use a service like my Deepl.io to act upon a Web-Hook that's triggered that service.
| require 'formula' | |
| class LibdnetPython <Formula | |
| depends_on 'libdnet' | |
| url 'http://libdnet.googlecode.com/files/libdnet-1.12.tgz' | |
| homepage 'http://code.google.com/p/libdnet/' | |
| sha1 '71302be302e84fc19b559e811951b5d600d976f8' | |
| def install | |
| ENV["CFLAGS"] = "-O3 -w -pipe" |