Twitter Buddy

Your personal Twitter/X assistant that automatically scrolls your timeline, collects tweets, analyzes trends with AI, and discovers accounts worth following — so you don't have to.

你的私人推特助手 — 自动帮你刷推特、采集推文、AI 分析趋势、发现值得关注的账号。

中文说明

What It Does

• Auto-collect tweets — Launches Chrome, switches to your "Following" timeline (sorted by latest), scrolls and saves every tweet with deduplication
• AI analysis — Periodically sends collected tweets to Claude for trend analysis, key highlights, and sentiment summary
• Account discovery — Scrolls the "For You" tab and uses AI to find high-quality accounts worth following, with follow-status detection and persistent user scoring
• Dashboard — Web UI to view analysis reports, discover reports, user score leaderboard, tweet volume charts, and trigger manual runs

Requirements

• Node.js 18+
• Google Chrome installed
• Anthropic API key

Setup

git clone https://github.com/YOUR_USERNAME/twitter-buddy.git
cd twitter-buddy
npm install
npx playwright install-deps

Create a .env file:

ANTHROPIC_API_KEY=sk-ant-xxxxx

Log in to Twitter (opens a Chrome window, log in manually, then close it):

npm run login

Usage

Daemon Mode (recommended)

Runs everything automatically — tweet collection, analysis every 2h, account discovery every 6h, plus a dashboard at http://localhost:3456:

npm run daemon

Individual Commands

Command	Description
npm run collect	One-time tweet collection
npm run collect:5	Quick collection (5 scrolls)
npm run analyze	Analyze recent 2h of tweets
npm run analyze:4h	Analyze recent 4h of tweets
npm run discover	Discover accounts from "For You"
npm run discover:50	Quick discovery (50 scrolls)
npm run dashboard	Start dashboard only
npm run login	Log in to Twitter

Dashboard

Open http://localhost:3456 after starting the daemon or dashboard.

• Analysis Reports — AI-generated trend reports with next auto-run countdown
• Discover — Account recommendations with follow status tags, "Run Now" button
• User Scores — Leaderboard of discovered accounts ranked by cumulative AI scores across runs
• Stats — Tweet volume charts by hour/day
• Tweet Data Files — Raw collected data

Configuration

Edit config.js to customize:

• scroll.* — Scroll speed, burst size, delays (for anti-detection)
• daemon.intervalMin/Max — Collection frequency (default: 5-60 min random)
• daemon.analysisIntervalMs — Analysis frequency (default: 2 hours)
• discover.intervalMs — Discovery frequency (default: 6 hours)
• discover.maxScrolls — How far to scroll "For You" (default: 100)
• analysis.model / discover.model — Claude model to use
• analysis.prompt / discover.prompt — Custom AI prompts

Account Discovery Details

The discover feature goes beyond simple recommendations:

• Follow-status detection — Automatically detects which accounts you already follow. Uses a two-phase approach: first hovering over avatars on the timeline to trigger profile cards (fast, no navigation), then visiting profile pages for any remaining unchecked users
• Persistent user scoring — Each discovered account receives a score from -5 to +5 per run based on content quality. Scores accumulate across runs, building a long-term quality signal. High-scoring accounts get prioritized in future reports
• Score leaderboard — Dashboard shows a ranked table of all scored users with cumulative scores, appearance count, latest evaluation, and links to their profiles
• Smart context — Historical scores are fed back to the AI on subsequent runs, helping it make more informed recommendations over time

Data Storage

All data is stored locally in the data/ directory:

data/
├── tweets/          # tweets_YYYY-MM-DD.json (per-day, deduplicated)
├── analysis/        # analysis_YYYY-MM-DD-HH-MM.md
├── discover/        # discover_YYYY-MM-DD-HH-MM.md
│   └── user_scores.json  # persistent user scoring data
└── state.json       # daemon state (last run times, gaps, etc.)

Running on a Server

Windows Server (with desktop) — Works out of the box. RDP in, run npm run login, then npm run daemon.

Headless Linux VPS — Use xvfb for a virtual display:

sudo apt install -y xvfb google-chrome-stable
npx playwright install-deps
xvfb-run node daemon.js

Tech Stack

• Playwright — Browser automation
• Claude API — AI analysis
• Vanilla Node.js HTTP server — Dashboard (zero dependencies)

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中文说明

你的私人推特助手 — 自动帮你刷推特、采集推文、AI 分析趋势、发现值得关注的账号。

功能

• 自动采集推文 — 启动 Chrome，切到 "Following" 时间线（最新排序），自动滚动采集，按天去重保存
• AI 分析 — 定时把采集到的推文发给 Claude 分析，输出热点话题、重点推文、情绪倾向
• 账号发现 — 自动刷 "为你推荐" 标签页，用 AI 找出值得关注的高质量账号。自动检测关注状态，跨轮次持久化评分
• Dashboard — 网页界面查看分析报告、发现报告、用户评分排行榜、推文数量图表，支持手动触发

快速开始

# 安装
npm install
npx playwright install-deps

# 配置 API Key
echo "ANTHROPIC_API_KEY=sk-ant-xxxxx" > .env

# 登录推特（手动登录后关闭浏览器）
npm run login

# 启动守护进程（全自动）
npm run daemon

打开 http://localhost:3456 查看 Dashboard。

命令一览

命令	说明
npm run daemon	守护进程（采集 + 分析 + 发现 全自动）
npm run collect	单次采集推文
npm run analyze	分析最近 2 小时推文
npm run discover	发现值得关注的账号
npm run dashboard	只启动 Dashboard
npm run login	登录推特

部署

• Windows Server（带桌面）— 直接跑，没问题
• Linux VPS（无屏幕）— 用 xvfb-run node daemon.js

账号发现机制

• 关注状态检测 — 自动识别你已关注的账号。先通过悬停头像触发 HoverCard 快速检测，剩余的再访问主页兜底
• 持久化评分 — 每次发现运行时，AI 会对每个未关注账号打分（-5 到 +5）。分数跨轮次累积，形成长期质量信号
• 评分排行榜 — Dashboard 中可查看所有被评分用户的排名、累积分数、出现次数、最近评语
• 历史上下文 — 历史评分会反馈给 AI，帮助后续推荐更精准

数据安全

所有数据本地存储，不上传任何地方。.env（API Key）和 .chrome-profile（登录态）已在 .gitignore 中排除。