Twitter Watch Agent Skill
提取一系列 Twitter 推文的互动数据并整合生成报告
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/cafe3310/public-agent-skills --skill twitter-watchThe instruction itself
5 sections, as written by the authortwitter-watch
一个自动监控 Twitter 互动数据的 Agent 技能，旨在通过模拟真人行为获取最准确的推文表现指标。
工作原理与设计意图
为了确保抓取成功率并规避反爬虫机制，watch.py 脚本采用了以下设计：
- 自动配置: 脚本启动时会自动检查并确保
~/.agent-browser/config.json中配置了{"autoConnect": true}，这确保了 agent-browser 优先尝试连接用户已打开的真实浏览器。 - 强制有头模式: 所有命令均附带
--headed参数，确保浏览器界面可见，方便用户监控和必要时介入（如处理验证码）。 - 真实浏览器验证: 脚本会检查
navigator.userAgent。如果仍处于Headless模式或未建立连接，脚本将发出警示。 - 持久化会话: 使用
--session-name twitter-watch。如果用户已在浏览器登录，脚本将继承登录状态。 - 拟人化滚动与随机延迟: 模拟真实用户行为，触发推文动态加载。
使用方法
1. 对非技术用户的说明 (当用户询问如何使用时)
如果用户询问如何使用此功能，请务必提供以下简洁的操作指南：
> Twitter 监控使用说明：
> 1. 开启浏览器调试模式：在 Chrome 地址栏输入 chrome://inspect/#remote-debugging 并回车，确保勾选 "允许远程调试"。
> 2. 准备环境：脚本会自动为您配置 agent-browser。在使用过程中，如果 Chrome 弹出“是否允许远程调试”提示，请务必点击“允许”。
> 3. 准备链接文件：将想要监控的 Twitter 链接放入文本文件（如 links.txt），每行一个。
> 4. 发送文件路径：将文件路径发送给我，我将自动抓取数据并生成 twitter_report.md 报告。
2. 执行流程 (Agent 必读)
- 环境准备: 确保已安装
agent-browser和python3。 - 人工验证:
- 首先运行：
agent-browser --headed --session-name twitter-watch open https://www.google.com。 - 使用
ask_user确认用户已看到窗口并允许连接。 - 启动监控:
python3 skills/twitter-watch/scripts/watch.py links.txt
输出规范
1. 单条结果 (JSON)
文件名：output_<tweet_id>.json
包含 raw (原文) 和 val (数值) 字段。
2. 汇总报告 (Markdown)
文件名：twitter_report.md
包含操作系统信息、生成时间以及带有格式化数字的表格。
环境要求
- Python 3.6+
- Node.js & NPM
- agent-browser CLI
- Google Chrome 浏览器 (已启用远程调试)
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How to use it
Take cafe3310/twitter-watch from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.