Catering Review Response Assistant
Paste the following prompt into your AI chat to install this skill:
Install @user_38f0802a/catering-review-response using https://skillhub.cn/install/skillhub.md.
About this skill
Problem it solves
Restaurant teams often receive negative reviews on platforms such as Meituan, Dianping, and Ele.me. Public responses can either reassure potential customers or escalate the incident. Weak replies tend to be generic, defensive, or accidentally share contact details, which may turn a complaint into a visible brand issue.
How it works
The skill first classifies the review: genuine complaint, exaggerated complaint, emotional venting, malicious review, or silent one-star feedback. It then drafts multiple options based on platform rules and business type. Key steps include:
- Collecting the original review, platform, cuisine category, and factual accuracy before choosing tone and compensation.
- Selecting from apology, explanation, or compensation structures and producing two to three comparable drafts.
- Covering common scenarios such as taste, slow service, staff behavior, hygiene issues, and delivery damage.
- Checking platform constraints, including character limits, contact-info rules, and prohibited actions like review manipulation or privacy leaks.
Boundaries
It generates response drafts and appeal guidance, not legal advice or final platform rulings. For refunds, compensation, or hygiene risks, confirm actual remediation with the store owner first. For malicious reviews, preserve evidence and follow the platform process.
Use Cases
- After receiving negative reviews on Meituan or Dianping, generate multiple publishable replies based on the review and business type.
- Draft apology, explanation, and compensation wording for slow serving, poor service, or delivery damage complaints.
- Check platform character limits and contact-info rules before publishing, while avoiding prohibited review-manipulation language.
- When a review appears malicious, prepare an evidence checklist such as order records and chat screenshots for a platform appeal.
Best For
- Restaurant managers: handle public negative reviews and reduce the risk of follow-up complaints.
- Store operations staff: respond to reviews across platforms while keeping brand tone consistent.
- Delivery operations owners: address delivery damage, missing items, and order-related complaints.
- Customer service supervisors: review response drafts for platform compliance and service boundaries.
Related Skills
AI agent tool for generating HTML proposals for client visit business scenarios, featuring deep research and dynamic mainline mapping.
Bid Proposal Verification Tool is used to verify the consistency between bid proposals and tender documents, checking table of contents, page numbers, attachments, and seals, based on Shibot Technology's bid data API.
An AI engine built on extensive bidding data to precisely search for tender projects and potential clients using natural language or structured criteria.
Automates bid document, response table, and material list generation from bid files and enterprise data using Shibuo Technology API.