X Algorithm Toolkit
Tweet scoring using X's actual algorithm weights - 22 signals, 18 filters, 11 tools
README
⚡ X Algorithm Toolkit
Score, optimize, and generate tweets using the actual signal weights from X's open-source recommendation algorithm.
🧠 What This Does
This toolkit reverse-engineers X's recommendation algorithm from the open-source codebase and gives you:
- Tweet Scorer — Score any draft (0-100) against the actual algorithm weights
- Hook Analyzer — Test your opening line against the -11×
not_dwelledpenalty - Diversity Calculator — Plan posting cadence using the decay formula from
author_diversity_scorer.rs - 18 Filter Checker — Run tweets through quality/safety gates
- AI Rewrite, Generate & Thread Builder — Multi-provider AI (Groq, Gemini, OpenAI, Claude)
- Draft Manager, Compare Mode, Score History — Full workflow tools
- Export Scorecard — Branded PNG downloads
📊 The 22 Algorithm Signals
From weighted_scorer.rs + ranking_scorer.rs:
| Signal | Weight | What It Means |
|---|---|---|
| Reply | 27.0× | #1 signal — end every post with a question |
| Bookmark | 10.0× | Save-worthy content gets massive boost |
| Follow | 4.0× | "I want more" — the career signal |
| Dwell (Binary) | 2.0× | Multi-line posts earn more read time |
| Cont. Dwell Time | 1.5× | Longer reads score higher |
| Click-Dwell Time | 1.5× | Deep interest after expanding |
| Report | -369× | Nuclear penalty — content becomes invisible |
| Not Interested | -74× | Off-topic = algorithmic death |
| Scrolled Past | -11× | Weak hooks trigger this |
+ 13 more signals (Like, Repost, Quote, Quoted Click, Share, DM Share, Copy Link, Click, Profile Click, Photo Expand, Video Quality View)
🚀 Quick Start
# Clone
git clone https://github.com/MrChartist/x-algorithm-toolkit.git
cd x-algorithm-toolkit
# Install & Run
npm install
npm run dev
Open http://localhost:5173 — no API key needed for scoring, filters, and analysis.
For AI features (Rewrite, Generate, Thread), add an API key in Settings (Groq free tier recommended).
🔧 MCP Server (npm)
Install the MCP server to connect the algorithm engine to any AI assistant:
Option 1: Via npx (Recommended)
Add to claude_desktop_config.json:
{
"mcpServers": {
"x-algorithm": {
"command": "npx",
"args": ["-y", "x-algorithm-mcp"]
}
}
}
Option 2: Global Install
npm install -g x-algorithm-mcp
Option 3: From Source
cd mcp && npm install && npm run build
11 Tools: score_tweet, check_filters, analyze_hook, get_signals, get_optimal_schedule, compare_tweets, detect_spam_patterns, diversity_penalty, classify_niche, get_thread_strategy, full_audit
3 Resources: x-algorithm://weights, x-algorithm://filters, x-algorithm://niches
🎯 AI Skill (Antigravity / Gemini CLI)
400+ lines of domain expertise that makes any AI an X algorithm expert:
Install Globally
mkdir -p ~/.gemini/antigravity/skills/x-algorithm-expert
curl -o ~/.gemini/antigravity/skills/x-algorithm-expert/SKILL.md \
https://raw.githubusercontent.com/MrChartist/x-algorithm-toolkit/master/skill/SKILL.md
What's Covered:
- All 22 signal weights with optimization strategies
- Phoenix Grok-based transformer architecture
- 77+ topic categories from
topic_ids_filter.rs - 10-point scoring system with letter grades
- Hook writing rules and 7 templates
- Author diversity decay formula
- OON viral mechanics
- Thread building strategy (6 templates)
- 18 safety filter checklist
- Niche-specific optimization (7 niches)
📁 Architecture
x-algo-toolkit/
├── src/ # React Web App (13 tabs)
│ ├── engine/ # Scoring engine + AI abstraction
│ └── components/ # 15 UI components
├── mcp/ # MCP Server (11 tools, 3 resources)
│ ├── src/ # TypeScript source
│ ├── dist/ # Compiled output
│ └── package.json # npm: x-algorithm-mcp
├── skill/ # AI Skill
│ └── SKILL.md # 400+ line expertise file
└── public/ # Static assets
🛠️ Tech Stack
- Frontend: React 19, TypeScript, Vite
- Animations: Framer Motion
- AI: Multi-provider (Groq/Gemini/OpenAI/Claude)
- MCP:
@modelcontextprotocol/sdkv1.12+ - Storage: localStorage (no backend needed)
📜 License
MIT — Built by @Mr_Chartist
Data sourced from X's open-source algorithm: weighted_scorer.rs, ranking_scorer.rs, author_diversity_scorer.rs, oon_scorer.rs, topic_ids_filter.rs, recsys_model.py
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。