Babysitter Incremental Model Strategy Selector

Selects and configures optimal incremental model strategies

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 "$T/library/specializations/data-engineering-analytics/skills/incremental-model-strategy-selector" ~/.claude/skills/a5c-ai-babysitter-incremental-model-strategy-selector && rm -rf "$T"

manifest: library/specializations/data-engineering-analytics/skills/incremental-model-strategy-selector/SKILL.md

Incremental Model Strategy Selector

Overview

Selects and configures optimal incremental model strategies. This skill optimizes data transformation efficiency through proper incremental processing patterns.

Capabilities

Incremental strategy selection (append, merge, delete+insert)
Partition pruning optimization
Unique key configuration
On_schema_change handling
Full refresh scheduling
Lookback window optimization
Late-arriving data handling

Input Schema

{
  "modelCharacteristics": {
    "sourceType": "string",
    "updatePattern": "append|update|delete",
    "volumeGB": "number",
    "updateFrequency": "string"
  },
  "platform": "snowflake|bigquery|redshift",
  "existingModel": "object"
}

Output Schema

{
  "strategy": "append|merge|delete+insert",
  "config": "object",
  "partitionStrategy": "object",
  "refreshSchedule": "object",
  "dbtConfig": "object"
}

Target Processes

Incremental Model Setup
dbt Model Development
Pipeline Migration

Usage Guidelines

Analyze source data update patterns
Measure data volume and update frequency
Select strategy based on characteristics
Configure appropriate lookback windows

Best Practices

Use append for insert-only sources
Use merge for sources with updates
Configure partition pruning for large tables
Schedule periodic full refreshes for data correction
Handle late-arriving data with appropriate lookback