restaurant-crosscheckCross-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.
Install via ClawdBot CLI:
clawdbot install liyang2016/restaurant-crosscheckGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
exec(Calls external URL not in known-safe list
https://www.dianping.comAI Analysis
The skill explicitly describes web scraping Dianping and Xiaohongshu, which involves sending user-provided location and cuisine data to external, unauthorized servers not under the skill provider's control. While consistent with the stated purpose, this data collection method lacks transparency on data handling and may violate platform terms of service, posing a privacy risk.
Audited Apr 16, 2026 · audit v1.0
Generated Mar 20, 2026
Tourists in Chinese cities use this skill to find highly-rated and consistent restaurant recommendations validated across Dianping and Xiaohongshu, ensuring trustworthy dining options in unfamiliar locations. It helps filter out overhyped spots by cross-referencing ratings and engagement metrics from both platforms.
Residents in urban areas leverage the skill to discover new or trending restaurants in their district, using consistency scores to avoid places with conflicting reviews. It aids in making informed choices for special occasions or everyday meals by analyzing platform data.
Content creators and food bloggers use the skill to verify restaurant quality before posting reviews, ensuring their recommendations align with broader public sentiment from Dianping and Xiaohongshu. This enhances credibility by cross-checking ratings and engagement trends.
Business travelers in China utilize the skill to quickly find reliable restaurants near their meetings or hotels, prioritizing high-confidence recommendations with consistency scores to save time and ensure satisfactory meals during trips.
Restaurant owners or investors employ the skill to analyze competitor performance and customer sentiment across platforms, identifying trends and validating quality for strategic decisions like menu changes or new locations.
Offer basic restaurant cross-check queries for free with rate limits, and charge for premium features like higher query volumes, advanced filters, or historical data access. Revenue comes from subscription tiers targeting businesses and developers.
Sell aggregated and analyzed restaurant data to food delivery apps, travel agencies, or marketing firms, providing validated recommendations and trend reports. Revenue is generated through licensing fees and custom analysis projects.
License the skill to travel and navigation apps as an in-app feature, where users pay for premium access or it drives ad revenue through increased engagement. Revenue shares come from app partnerships and in-app purchases.
💬 Integration Tip
Ensure robust proxy management and error handling to mitigate scraping blocks from Dianping and Xiaohongshu, and optimize fuzzy matching thresholds for accurate cross-platform restaurant identification.
Scored Jun 17, 2026
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