dianpingv0.1.0

Users seek restaurants for specific events like dates, family gatherings, or business dinners. The skill analyzes Dianping ratings, reviews, and photos to match venues with the occasion's requirements, such as ambiance, service quality, and menu suitability, avoiding generic high-score recommendations.

Users look for cafés based on needs like remote work, socializing, or quiet relaxation. The skill evaluates reviews for practical signals like noise levels, seating comfort, and power outlets, distinguishing between photogenic spots and functional ones for long stays.

Users assess deals or packages for services such as massages, beauty treatments, or KTV. The skill checks constraints like time limits, hidden fees, and user treatment to determine if a deal offers genuine value and fits practical needs beyond just low price.

Users provide review excerpts or screenshots to identify fake reviews or common complaints. The skill analyzes patterns in negative and recent reviews to highlight recurring issues like poor hygiene, long waits, or upselling, helping users make informed decisions.

Offers advanced analytics like trend detection, personalized recommendations, and ad-free browsing for a monthly fee. Revenue comes from user subscriptions, targeting frequent Dianping users who need deeper insights beyond basic ratings.

Partners with restaurants and service providers to promote deals or packages, earning commissions on user purchases. Integrates seamlessly with Dianping listings to highlight verified offers, driving sales while providing value-added recommendations.

Sells aggregated insights from review analysis to merchants, helping them improve services, identify trends, and monitor competition. Revenue is generated through B2B contracts, leveraging the skill's ability to parse large volumes of user feedback.