A comprehensive social media intelligence center providing multi-platform scraping, structured data analysis, and AI-powered trend insights.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install social-intel
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install social-intel using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Social Intel Hub?
Social Intel Hub is a sophisticated Openclaw Skills asset designed to transform raw social media data into actionable intelligence. By integrating multiple platforms like Xiaohongshu, Weibo, Bilibili, and TikTok into a unified workflow, it allows developers and researchers to extract structured data, perform sentiment analysis via word clouds, and track engagement metrics through a centralized command-line interface.
This skill leverages the TikHub MCP for seamless, login-free data acquisition across seven major platforms. It bridges the gap between raw web scraping and high-level data storytelling, providing not just the numbers, but the AI-ready prompts needed for deep qualitative insights. Whether you are monitoring brand health or scouting for emerging trends, this tool streamlines the entire social intelligence lifecycle.
Social Intel Hub Use Cases
- Competitive analysis comparing brands or topics across XHS, Weibo, and Bilibili.
- Generating visual word clouds to identify high-frequency keywords in social conversations.
- Tracking 7-day engagement trends to identify rising or declining viral topics.
- Bulk harvesting comments from specific posts for sentiment research and audience feedback.
- Exporting multi-platform datasets to Excel or CSV for integration into business intelligence tools.
How Social Intel Hub Works
- The user provides a natural language query or command specifying keywords, platforms, and analysis depth.
- The system invokes the social_intel.py script, which determines the optimal data source (TikHub MCP or local 24-hour cache).
- Raw data is fetched across the requested platforms (e.g., likes, bookmarks, views, and comments).
- The data engine processes the raw output to calculate averages, identify top-performing posts, and aggregate hashtags.
- Visualization modules generate word clouds and trend charts, while the script prepares an AI prompt for advanced LLM analysis.
- The final output is displayed in the terminal and saved to the specified export format (CSV, Excel, or PNG).
Social Intel Hub Setup
To install this skill, ensure you have Python 3 and the required dependencies installed on your system. Run the following command to set up the necessary libraries:
pip3 install wordcloud matplotlib openpyxl
Ensure that the core script is located within your Openclaw Skills workspace directory at /Users/kk/.openclaw/workspace/skills/social-intel/social_intel.py.
Social Intel Hub Data Schema & Taxonomy
Social Intel Hub organizes data into a structured hierarchy for easy analysis:
| Data Type | Attributes | Output Format |
|---|---|---|
| Global Metrics | Total likes, bookmarks, views, comments, and averages | Terminal / Excel |
| Topic Analysis | TOP 20 hashtags and frequency counts | PNG Wordcloud |
| Leaderboard | TOP 3 posts by engagement, likes, and reach | Markdown Report |
| Trend Data | Daily engagement aggregation over the last 7 days | Line/Bar Charts |
| Raw Exports | Full post data including IDs, URLs, and captions | CSV / Excel |
Social Intel Hub Advanced Features
- Parallel scraping mode to query all supported platforms simultaneously with a single command.
- Smart 24-hour caching mechanism to reduce API overhead and improve performance for repeat queries.
- Multi-keyword comparative analysis to benchmark different topics against each other.
- Automated AI insight generation that creates pre-formatted prompts for LLM-based qualitative analysis.
- Comprehensive export engine supporting simultaneous CSV and Excel output for data portability.
SKILL.md
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