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sunfang1cn

social-favorites-to-obsidian

by sun fang · GitHub ↗ · v1.0.1 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install xhs-zh-sync-obsidian
Description
将小红书和知乎收藏增量同步到 Obsidian:依赖 hctec-* 抓取技能,使用 CookieCloud 登录态,支持首次安装、依赖检查、分类规则、Markdown 导出和 OpenClaw 定时任务生成。当用户要安装、配置、诊断、归档、分类、导出或定时同步社交平台收藏到 Obsidian 时使用。
README (SKILL.md)

Social Favorites to Obsidian

这个技能把“小红书/知乎收藏 -> 抓取 -> 分类 -> Obsidian 导出 -> 定时同步”做成可发布的安装流程。平台抓取由 hctec 原子技能负责,本技能负责安装引导、配置、状态、分类、导出和 cron 生成。

工作流

  1. 首次安装时不要直接使用默认值开跑。先读取 references/first-install.md,并向用户确认这些可选项:
    • CookieCloud 服务端:本机 Docker 安装,还是使用已有远程服务端;远程服务端需要地址、UUID 和 Password。
    • Obsidian vault:自动创建并使用官方 Obsidian Sync,自动创建但只本地导出,还是使用已有本地 vault 目录。
    • 官方 Obsidian Sync:需要 Obsidian 账号邮箱/用户名、登录密码或交互登录、远程 vault 名字或 ID,必要时还要端到端加密密码。
    • 分类标准:由 LLM 初始化生成分类规则,还是用户稍后自行编辑。
  2. 收集完首次安装选项后,再运行安装和初始化命令。例如:
    python install.py
    
    如果安装环境只能调用 scripts 目录,也可以运行:
    python scripts/interactive_install.py
    
    非交互拆分安装时再使用底层命令:
    python scripts/setup.py --init --install-skill-deps --install-python-deps --install-playwright
    
  3. 安装 hctec 第三方技能后,必须运行一次知乎格式补丁,避免知乎正文 plain 文本丢失段落和换行:
    python scripts/patch_hctec_zhihu_format.py
    
    详见 references/dependencies.md
  4. 首次安装时按用户选择部署 CookieCloud 服务端并安装浏览器插件。详见 references/auth.md
  5. 如果 CookieCloud 服务端不在运行本技能的机器上,用 --cookiecloud-server-url http://\x3C服务器IP>:8088 初始化,或让用户手动填写 COOKIECLOUD_SERVER_URLCOOKIECLOUD_UUIDCOOKIECLOUD_PASSWORD
  6. 首次安装时按用户选择配置 Obsidian 同步方式。官方 Sync 走 obsidian-headlessob loginob sync-setup;本地模式则只初始化本地目录。详见 references/obsidian-sync.md
  7. agent 判断是否首次安装时,运行:
    python scripts/setup.py --status --json
    
  8. 检查配置:
    python scripts/setup.py --doctor
    
  9. 同步并导出:
    python scripts/sync.py --platform xhs
    python scripts/sync.py --platform zhihu
    python scripts/export_obsidian.py --platform all --incremental
    
  10. 如果用户要自动化,生成 OpenClaw cron 配置:
python scripts/install_cron.py --platform xhs --time 06:00 --print
python scripts/install_cron.py --platform zhihu --time 05:00 --print

按需阅读

  • 首次安装访谈和选项决策:references/first-install.md
  • 首次安装和外部依赖:references/dependencies.md
  • CookieCloud 服务端、浏览器插件和 cookie 兜底:references/auth.md
  • 配置字段:references/config.md
  • Obsidian Headless Sync 和本地目录模式:references/obsidian-sync.md
  • 定时任务:references/cron.md
  • Obsidian 目录和分类:references/obsidian-layout.md

安全

不要把用户数据发布进技能包:cookiecloud.env、原始 Cookie、状态文件、日志、已下载笔记、图片、Obsidian 导出内容都只能作为运行时数据保存在用户本机。

Usage Guidance
Before installing, confirm you trust the package and the external hctec GitHub skills, review or pin those dependencies, use the least-sensitive accounts/sessions possible, keep cookiecloud.env and the data/vault folders private, and review any generated cron job before enabling automatic sync.
Capability Assessment
Purpose & Capability
The stated purpose matches the artifacts: syncing Xiaohongshu/Zhihu favorites to Obsidian requires cookies, local exports, optional Obsidian Sync, and scheduled sync. These capabilities are sensitive but mostly disclosed.
Instruction Scope
The instructions generally require user confirmation before first install and before choosing CookieCloud, Obsidian, classification, and cron options. Generated cron commands should still be reviewed before enabling.
Install Mechanism
The install flow downloads unpinned third-party hctec skills from GitHub into the OpenClaw skills workspace and uses other external installers/images. This is purpose-aligned but creates a material supply-chain review issue because those dependencies may run with the user’s cookies.
Credentials
Registry metadata declares no required binaries, env vars, or credentials, while the README and scripts require Python, Docker/Compose or a remote CookieCloud server, optional Node/npm/obsidian-headless, Playwright, and account/session credentials. The docs disclose this, but the metadata is under-declared.
Persistence & Privilege
The skill stores configuration, CookieCloud credentials, raw/export state, downloaded media, and optional cron specs locally; Docker CookieCloud may restart unless stopped. This is disclosed and purpose-aligned, but persistent.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install xhs-zh-sync-obsidian
  3. After installation, invoke the skill by name or use /xhs-zh-sync-obsidian
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
Version 1.0.1 - No functional changes; documentation only. - SKILL.md has been reformatted with no updates to content or workflow. - No file changes detected in this release.
v1.0.0
- Initial release of social-favorites-to-obsidian skill. - Enables incremental sync of Xiaohongshu and Zhihu favorites to Obsidian. - Supports guided installation, dependency checks, classification rules, and Markdown export. - Integrates with CookieCloud for authentication and with hctec-* skills for content fetching. - Allows configuration of both local and Obsidian Sync export modes. - Provides OpenClaw cron generation for scheduled sync and export.
Metadata
Slug xhs-zh-sync-obsidian
Version 1.0.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is social-favorites-to-obsidian?

将小红书和知乎收藏增量同步到 Obsidian:依赖 hctec-* 抓取技能,使用 CookieCloud 登录态,支持首次安装、依赖检查、分类规则、Markdown 导出和 OpenClaw 定时任务生成。当用户要安装、配置、诊断、归档、分类、导出或定时同步社交平台收藏到 Obsidian 时使用。 It is an AI Agent Skill for Claude Code / OpenClaw, with 113 downloads so far.

How do I install social-favorites-to-obsidian?

Run "/install xhs-zh-sync-obsidian" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is social-favorites-to-obsidian free?

Yes, social-favorites-to-obsidian is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does social-favorites-to-obsidian support?

social-favorites-to-obsidian is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created social-favorites-to-obsidian?

It is built and maintained by sun fang (@sunfang1cn); the current version is v1.0.1.

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