A professional evaluation system for catering entrepreneurs to scientifically assess site selection, calculate payback periods, and identify business risks.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install restaurant-evaluator
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 restaurant-evaluator 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 Restaurant Evaluator?
The Restaurant Evaluator is a specialized expert system designed for the catering industry, modeled after the methodologies of Yongge Catering Entrepreneurship. It functions as a comprehensive self-assessment tool that helps entrepreneurs move beyond intuition and make data-driven decisions. By integrating with Openclaw Skills, this tool provides a structured framework for evaluating the six dimensions of site quality, ensuring that every potential location meets mandatory safety and legal standards before investment.
This skill is particularly valuable for identifying high-risk business models and calculating complex financial metrics such as net profit margins and multi-month payback periods. Whether you are planning a small couple-run shop or a specialized single-product outlet, the Restaurant Evaluator provides the technical rigor needed to minimize risk in the competitive food and beverage market.
Restaurant Evaluator Use Cases
- Evaluating the quality of catering site locations based on foot traffic and customer demographics.
- Calculating the expected return on investment (ROI) and monthly net profit for new restaurant ventures.
- Performing a feasibility study for opening a store based on capital, product, and operational constraints.
- Identifying and avoiding common catering pitfalls like quick-招 franchise traps and high-dependency chef models.
- Selecting the most appropriate business model, such as the Breakfast Shop or the Low-Price High-Volume model.
How Restaurant Evaluator Works
- The AI initiates a questionnaire to gather critical site data including property rights, utilities, and fire safety compliance.
- Users input core metrics such as daily average flow (e.g., 2000+ for commercial areas) and rent-to-revenue ratios.
- The system validates the mandatory pass items; if any baseline safety or legal requirement is missing, the site is immediately flagged for abandonment.
- Using a weighted scoring engine, the skill processes dimensions like competition, visibility, and cost-return metrics.
- The tool generates a final assessment grade (A/B/C/D) and provides a detailed calculation of the months required to recoup the total investment.
Restaurant Evaluator Setup
To deploy the Restaurant Evaluator within your Openclaw Skills workflow, you can utilize the following configuration script to process site data. Ensure your environment has Python 3 installed for the evaluation logic:
# Define the site selection parameters in a JSON format
cat > /tmp/eval_input.json << 'EOF'
{
"location": {
"property_clear": true,
"license": true,
"ventilation": true,
"utilities": true,
"fire_safety": true,
"landlord": true,
"demolition_risk": false,
"daily_flow": 2500,
"customer_match": "match",
"rent_15_percent": true,
"contract_3y": true
}
}
EOF
# Run the evaluation script provided in the skill repository
python3 scripts/evaluate.py /tmp/eval_input.json
Restaurant Evaluator Data Schema & Taxonomy
The Restaurant Evaluator utilizes a multi-dimensional data schema to categorize site and business health. The evaluation is broken down into the following taxonomy:
| Dimension | Weight | Target Metric |
|---|---|---|
| Foundation | Mandatory | 7/7 Must-Pass Items (Property, License, etc.) |
| Traffic & Audience | 55 | Daily Flow + Customer Match |
| Visibility | 40 | Shop Front Prominence + Traffic Direction |
| Competition | 33 | Cluster Density + Controllability |
| ROI & Cost | 51 | Rent <= 15% + 3-Year Contract |
| Risk Management | 45 | Road Construction Risk + Non-Dead Corners |
Final scores determine the grading: A Grade (280+ points), B Grade (230-279 points), C Grade (180-229 points), and D Grade (<180 points).
Restaurant Evaluator Advanced Features
- Automated payback period calculator based on raw material costs, labor, and utilities.
- Intelligent pitfall identification for 5 'Deadly Models' including internet-famous concept stores and over-decorated shops.
- Strategic model matching for 4 'Winning Models' such as Couple Shops and single-product specialty stores.
- Decision-tree logic for entrepreneurship feasibility (The 3-Yes Rule).
- Integration-ready JSON output for multi-agent research within Openclaw Skills.
SKILL.md
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