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nanzhipro/README.md

nanzhi

Keep building.

Building native macOS tools, AI workflows, and durable knowledge systems.


关于我 / About

我主要在做三类事情:

  • macOS 原生应用与系统能力:偏爱 Swift、Apple 官方框架、原生体验和本地优先。
  • AI 工作流与技能系统:关注可恢复、可审计、可长期维护的 AI 协作方式。
  • 知识组织与文档工程:把一次性的输出,变成可以持续演进的结构化资产。

In short: I like building tools that are native, practical, local-first, and durable.

关注方向 / Focus

  • Swift / macOS / Apple 平台能力
  • AI-native workflow design
  • Local-first products
  • Markdown / wiki / spec-driven knowledge systems
  • Small tools with strong product taste

代表项目 / Featured Projects

Project What it is
Aegis macOS Endpoint Security Agent,关注目录级访问控制与系统原生安全边界
SnapSort AI-powered screenshot organization app for macOS
Karpathy-llm-wiki-bootstrap-skill 用 Markdown wiki 的方式构建可持续维护的 LLM 知识库
phase-contract-workflow-skill 让 AI 长任务具备分阶段、可恢复、可审计的执行结构
TextWeaver 基于文本与 AI 生成精美 HTML / PNG 的内容工作流
Lyrebird-Agent 探索简历背后的认知机制——通过多智能体协作提取认知模式,并配备实时监控控制台。

我在意的事情 / What I Care About

  • 原生体验优先:能不用 WebView,就尽量不用。
  • 本地优先:隐私、速度、掌控感都更好。
  • 结构胜过堆功能:好系统先有清晰边界,再谈扩展。
  • 让 AI 输出可沉淀:不只回答当下问题,也要留下可复用资产。

Tech Stack

Swift · Python · Ruby · TypeScript · Markdown

现在在做 / Currently Building

  • AI workflow / skill design
  • macOS native utilities
  • spec-driven project execution
  • knowledge-first tooling

如果你也在做 macOS 原生产品、AI 工作流、知识系统,欢迎来看看我的项目。
If you're building in similar areas, feel free to explore the repos.

Pinned Loading

  1. Karpathy-llm-wiki-bootstrap-skill Karpathy-llm-wiki-bootstrap-skill Public

    Installable skill + working example for building persistent, LLM-maintained Markdown wikis, based on Karpathy’s original LLM Wiki idea.

    Python 64 14

  2. karpathy-wiki karpathy-wiki Public

    its original source materials come from Karpathy's X posts and important talks.

    4 1

  3. vibe-coding-breath vibe-coding-breath Public

    AI is thinking, you are breathing

    1

  4. arc42-spec-skill arc42-spec-skill Public

    基于arc42,创建的架构沟通 spec 框架

    2 1

  5. phase-contract-workflow-skill phase-contract-workflow-skill Public

    把 AI 长任务的稳定性从模型记忆迁到仓库文件,让大型项目分阶段执行、可恢复、可审计

    Ruby 3