A professional-grade analytical tool designed to identify and quantify long-term structural competitive advantages in businesses.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install moat-evaluator
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install moat-evaluator using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Moat Evaluator is a specialized framework within the Openclaw Skills ecosystem dedicated to value investing analysis. It synthesizes the core principles of Warren Buffett's investment philosophy to evaluate the type, strength, and sustainability of a company's economic moat.
By assessing structural factors rather than temporary market trends, the tool provides a rigorous 25-point scoring system across five critical moat dimensions: Brand Power, Network Effects, Switching Costs, Cost Advantages, and Intangible Assets. It is designed for investors and analysts who need to distinguish between fleeting market hype and enduring long-term value.
To integrate Moat Evaluator with your AI agent, ensure you have the Openclaw Skills environment configured. Install the skill using the following command:
# Install the Moat Evaluator skill
openclaw install moat-evaluator
# Verify installation and check dependencies
openclaw verify --skill moat-evaluator
Configure your environment variables if you are connecting to external financial data providers for automated metric retrieval.
The skill utilizes a structured JSON schema for inputs and outputs to ensure compatibility across Openclaw Skills.
| Field | Type | Description |
|---|---|---|
company_name |
String | Legal name of the entity |
business_description |
String | Summary of the business model |
pricing_power |
Enum | Assessment of price elasticity (Yes/No/Unsure) |
moat_types |
Array | List of identified advantages with evidence and strength scores |
total_score |
Integer | Normalized score out of 25 |
trend |
String | Directional indicator (Widening, Stable, Narrowing) |
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