restaurant-review-crosscheck
Cross-reference restaurant recommendations from Xiaohongshu (小红书) and Dianping (大众点评) to validate restaurant quality and consistency. Use when querying restaurant recommendations by geographic location (city/district) to get validated insights from both platforms. Automatically fetches ratings, review counts, and analyzes consistency across platforms to provide trustworthy recommendations with confidence scores.
Why use this skill?
Validate restaurant quality by cross-referencing Dianping and Xiaohongshu. Get reliable dining recommendations with consistency scores for any location.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/liyang2016/restaurant-crosscheckWhat This Skill Does
The restaurant-review-crosscheck skill is a sophisticated intelligence tool designed for OpenClaw agents to perform comparative sentiment analysis on dining recommendations. By integrating data streams from Dianping (the authoritative source for ratings and pricing) and Xiaohongshu (the trendsetting source for user sentiment and visual engagement), this skill provides a holistic view of a restaurant's true quality. It automates the tedious manual labor of cross-referencing information, calculates a weighted recommendation score, and identifies inconsistencies—such as when a restaurant is highly rated on Dianping but criticized for a 'hype-only' experience on social media.
Installation
To integrate this skill into your agent, run the following command in your terminal:
clawhub install openclaw/skills/skills/liyang2016/restaurant-crosscheck
Ensure your agent environment has the necessary dependencies for scraping and that you have configured the required residential proxy settings for reliable data retrieval.
Use Cases
- Travel Planning: Quickly identify the best-rated, authentic eateries in a new city while filtering out tourist traps.
- Business Dinners: Ensure a venue is consistently well-regarded by both professional food critics and casual social media users to avoid embarrassing experiences.
- Market Research: Analyze dining trends in specific districts to understand which cuisines or restaurant styles are currently gaining the most traction.
Example Prompts
- "Find the top-rated Japanese restaurants in Shanghai's Jing'an district that have at least 100 reviews on Dianping and strong engagement on Xiaohongshu."
- "I am planning a hotpot dinner in Beijing's Chaoyang area. Cross-reference the best options and let me know which ones show high consistency across platforms."
- "Show me the 5 best-rated restaurants in Chengdu for Sichuan cuisine, and flag any that have a high rating on Dianping but low sentiment scores on Xiaohongshu."
Tips & Limitations
- Rate Limiting: This skill respects platform anti-scraping measures. When performing bulk queries, expect a latency of 2-3 seconds per request to ensure account safety.
- Matching Logic: The skill uses Levenshtein distance for name matching; however, extreme variations in naming may occasionally require manual verification.
- Data Freshness: Results depend on real-time availability of public platform data. If a platform changes its UI structure, the scraping scripts may require updates found in the skill's GitHub repository.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-liyang2016-restaurant-crosscheck": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: network-access, data-collection, external-api