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name: semantic-model-builder description: Create comprehensive semantic layer documentation for analytics assets. Use when documenting data models, defining business metrics, creating data dictionaries, or building context for AI-assisted analysis.

Semantic Model Builder

Quick Start

Build structured documentation that defines business metrics, data models, and relationships in a format optimized for AI-assisted analysis.

Context Requirements

1. Metric/Entity to Document: What needs documentation
2. Calculation Logic: How it's computed (SQL, formula, or plain English)
3. Business Context: Why it matters, how it's used
4. Data Sources: Where the data comes from

Context Gathering

Initial Prompt:

"Let's build semantic documentation. What would you like to document?

• A specific metric (e.g., MRR, DAU, Conversion Rate)
• A data model/table (e.g., users table, transactions)
• A business concept (e.g., 'Active Customer')
• Multiple related items"

For Metrics:

"For [metric name], I need:

1. Definition: What is this metric in plain English? Example: 'Monthly Recurring Revenue (MRR) is the predictable revenue generated each month from active subscriptions'

2. Calculation: How is it calculated?

   • Provide SQL query, OR
   • Formula (e.g., 'SUM(subscription_amount) WHERE status = active'), OR
   • Plain English steps

3. Business Context:

   • Why does this metric matter?
   • Who uses it?
   • What decisions does it inform?
   • What's a 'good' value?

4. Edge Cases (optional but helpful):

   • What should be included/excluded?
   • How to handle special situations?
   • Known calculation gotchas?"

For Data Models:

"For [table/model name], I need:

1. Purpose: What does this table represent? Example: 'One row per user signup'

2. Key Columns: Most important fields

   • Which are IDs/keys?
   • Which are metrics?
   • Which are attributes?

3. Relationships: How does this connect to other tables? Example: 'users.id → orders.user_id'

4. Grain: What is one row? Example: 'One row per transaction' or 'One row per user per day'"

For Business Concepts:

"For [concept], help me understand:

1. Definition: What is this?
2. How to Identify: How do you know something is/isn't this?
3. Related Data: Where is this captured in data?
4. Why It Matters: Business significance?"

Workflow

1. Gather Information

Start with what's provided, probe for gaps:

If user provides SQL: