A multi-platform sentiment monitoring and analysis tool for tracking brands and products across global and Chinese social media.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install sentiment-radar
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 sentiment-radar 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 Sentiment Radar?
Sentiment Radar is a comprehensive social listening skill designed to aggregate and analyze public opinion across diverse platforms. By leveraging MediaCrawler for Xiaohongshu (XHS) and Xpoz MCP for Twitter and Reddit, it provides a unified view of market perception.
This Openclaw Skills entry enables developers and marketers to move beyond raw data collection, offering structured insights into user pain points, pricing complaints, and competitive landscape analysis. It is specifically engineered to handle the nuances of different platforms, including localized engagement metrics and multi-language support.
Sentiment Radar Use Cases
- Monitoring competitor sentiment and market positioning in real-time.
- Tracking user reception and feedback during new product launches.
- Analyzing specific user pain points and feature requests across diverse social media channels.
- Generating automated market intelligence reports for stakeholders.
How Sentiment Radar Works
- Identify target products, brands, and search keywords for both Chinese and English platforms.
- Execute data collection using MediaCrawler for XHS and Xpoz MCP tools for Twitter and Reddit.
- Process the raw JSON data through the analysis script to categorize sentiment and extract product mentions.
- Generate a structured Markdown report that highlights engagement metrics, pricing complaints, and head-to-head comparison data.
Sentiment Radar Setup
First, clone the MediaCrawler repository into your Openclaw Skills workspace:
git clone https://github.com/NanmiCoder/MediaCrawler ~/.openclaw/workspace/skills/media-crawler
cd ~/.openclaw/workspace/skills/media-crawler
uv sync
playwright install chromium
Configure the base settings in config/base_config.py by setting ENABLE_CDP_MODE = True and SAVE_DATA_OPTION = "json". For Twitter and Reddit access, ensure Xpoz MCP is configured via mcporter with valid OAuth tokens located at ~/.mcporter/xpoz/tokens.json.
Sentiment Radar Data Schema & Taxonomy
The skill organizes its data into a structured hierarchy for easy analysis:
| Data Component | Description |
|---|---|
search_contents_YYYY-MM-DD.json |
Main post data including text, author info, and engagement metrics. |
search_comments_YYYY-MM-DD.json |
Associated user comments linked to specific posts for granular sentiment. |
report.md |
The final synthesized analysis report including sentiment ratios and pain points. |
Product Mapping |
A JSON-based configuration mapping keywords to specific product entities. |
Sentiment Radar Advanced Features
- CDP (Chrome DevTools Protocol) mode to bypass anti-detection mechanisms on sensitive platforms.
- Automated parsing of localized engagement counts, such as Chinese number formats.
- Multi-platform aggregation that combines data from Reddit, Twitter, and XHS into a single intelligence report.
- Specialized extraction of pricing and subscription complaints to identify market value perception.
- Support for background execution and QR code login flows for secure platform access.
SKILL.md
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