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小红书自动发布

作者 weishuai34-bit · GitHub ↗ · v1.2.0 · MIT-0
cross-platform ⚠ suspicious
116
总下载
0
收藏
0
当前安装
2
版本数
在 OpenClaw 中安装
/install xiaohongshu-publish-auto
功能描述
自动读取指定文件夹当日视频和标题,连接Chrome通过脚本将内容发布到小红书账号。
安全使用建议
This skill automates posting by controlling your Chrome browser via the remote debugging port — that means it will act as whatever Chrome profile is exposed (including using your logged-in accounts and cookies). Before installing: - Inspect and/or modify the code: change the hardcoded path /Users/today to a proper configurable path (e.g., process.env.HOME) or confirm it matches your environment. - Do not run this against your main Chrome profile. Start Chrome with a dedicated user-data-dir and only enable --remote-debugging-port for that profile, or run it in a throwaway profile. - Ensure Puppeteer and Node dependencies come from a trusted source; the package has no install spec for npm modules. - Be aware the script uses macOS-specific commands (open) and curl; it appears Mac-only. - Review the unexplained skill.json note about YouTube cookies — the runtime does not download videos, so confirm your workflow and privacy implications. - If you proceed, run in a controlled environment first, and avoid leaving the remote debugging port open after use.
功能分析
Type: OpenClaw Skill Name: xiaohongshu-publish-auto Version: 1.2.0 The skill is a browser automation tool designed to upload videos and titles to the Xiaohongshu (Red) creator platform. It uses Puppeteer to connect to a local Chrome instance via the remote debugging port (9222) and automates the file upload and form-filling process using local files from a specific directory. While it interacts with the user's active browser session and local filesystem, its behavior is entirely consistent with its stated purpose in SKILL.md and skill.json, with no evidence of data exfiltration, malicious execution, or prompt injection.
能力评估
Purpose & Capability
The code implements the stated purpose (read a local folder and drive Chrome to publish on 小红书 via Puppeteer). However the implementation is Mac-specific and uses a hardcoded path (/Users/today/Movies/小红书英语) rather than the user's HOME (~) declared in SKILL.md; skill.json mentions cookies and YouTube downloads even though the runtime code does not perform downloads. The metadata omits mention of required local commands (curl, open).
Instruction Scope
SKILL.md instructs to enable Chrome remote debugging and to place files in ~/Movies/..., which matches the high-level behavior, but the runtime script diverges: it uses a hardcoded user path (/Users/today), spawns local commands (curl and open) and saves screenshots to /tmp. The skill will control whatever Chrome profile is exposed to the remote debugging port (i.e., it will act as the logged-in user), which is a sensitive capability not emphasized in the docs.
Install Mechanism
There is no install spec even though the code requires Node.js modules (puppeteer). The manifest lists runtime: node but does not provide steps to install puppeteer or other npm deps. The script also expects system binaries (curl, open) and a Mac environment; these are not declared in requirements, which is an incoherence and operational risk.
Credentials
No environment variables or credentials are declared, which is consistent, but the skill depends on an already-authenticated Chrome session (it uses Chrome's cookies/profile via remote debugging). That gives the skill access to session cookies and any logged-in accounts in that profile. skill.json also mentions 'cookies' for YouTube downloads, which the code does not perform — an unexplained requirement.
Persistence & Privilege
The skill does not request always:true and does not modify other skill configurations. However enabling Chrome with --remote-debugging-port exposes the browser profile to external control while the port is open; the script starts Chrome with that flag (or connects if already running), so the effective privilege is broad during execution. This is a legitimate need for Puppeteer automation but is high-impact and should be limited to a dedicated browser profile.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install xiaohongshu-publish-auto
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /xiaohongshu-publish-auto 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.2.0
支持持久化登录,账号长期在线
v1.1.0
小红书自动发布 1.1.0 更新日志 - 新增自动读取当天视频及标题文件并发布到小红书的功能 - 明确指定视频和标题文件存放路径及命名规范 - 标题文件支持正文和 # 开头的话题自动提取 - 提供详细使用指南与注意事项,包括清空话题区及 Chrome 调试模式要求 - 支持通过关键词语音触发自动发布
元数据
Slug xiaohongshu-publish-auto
版本 1.2.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

小红书自动发布 是什么?

自动读取指定文件夹当日视频和标题,连接Chrome通过脚本将内容发布到小红书账号。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 116 次。

如何安装 小红书自动发布?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install xiaohongshu-publish-auto」即可一键安装,无需额外配置。

小红书自动发布 是免费的吗?

是的,小红书自动发布 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

小红书自动发布 支持哪些平台?

小红书自动发布 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 小红书自动发布?

由 weishuai34-bit(@weishuai34-bit)开发并维护,当前版本 v1.2.0。

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