Babysitter SCD Implementation Generator

Generates Slowly Changing Dimension implementations across platforms

install

source · Clone the upstream repo

git clone https://github.com/a5c-ai/babysitter

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/data-engineering-analytics/skills/scd-implementation-generator" ~/.claude/skills/a5c-ai-babysitter-scd-implementation-generator && rm -rf "$T"

manifest: library/specializations/data-engineering-analytics/skills/scd-implementation-generator/SKILL.md

SCD Implementation Generator

Overview

Generates Slowly Changing Dimension implementations across platforms. This skill automates the creation of SCD patterns for proper historical tracking.

Capabilities

SCD Type 1/2/3/4/6 implementation
MERGE statement generation
dbt snapshot configuration
Historical tracking optimization
Surrogate key management
Effective date handling
Current flag management
Mini-dimension design

Input Schema

{
  "dimension": {
    "name": "string",
    "columns": ["object"],
    "businessKey": ["string"]
  },
  "scdType": "1|2|3|4|6",
  "platform": "snowflake|bigquery|redshift|dbt",
  "trackingColumns": ["string"]
}

Output Schema

{
  "ddl": "string",
  "mergeStatement": "string",
  "dbtConfig": "object",
  "documentation": "string"
}

Target Processes

SCD Implementation
Dimensional Model Design
dbt Model Development

Usage Guidelines

Define dimension structure with business keys
Select appropriate SCD type for business requirements
Specify target platform for syntax generation
Identify columns to track for historical changes

Best Practices

Use SCD Type 2 for attributes requiring full history
Implement surrogate keys for dimension tables
Use effective dates rather than just current flags
Consider mini-dimensions for rapidly changing attributes
Test SCD logic with representative change scenarios