What problem does it solve? Building OmniStudio Data Mappers (formerly DataRaptors) by hand is error-prone: wrong type selection, missing field mappings, unbounded queries, and FLS violations cause runtime failures and governor limit issues. This Skill generates production-ready Extract, Transform, Load, and Turbo Extract configurations and scores them against a 100-point quality rubric before deployment. ## Core Features & Use Cases - Data Mapper Generation: Creates OmniDataTransform and OmniDataTransformItem records from JSON templates for Extract, Turbo Extract, Transform, and Load types with correct naming conventions (DR_[Type][Object][Purpose]). - Validation & Scoring: Scores configurations across 5 categories (Design & Naming, Field Mapping, Data Integrity, Performance, Documentation) with deploy/review/block thresholds at 90+, 67-89, and below 67. - Anti-Pattern Guardrails: Blocks wildcard field extraction, unbounded queries, missing lookup resolution, hardcoded record IDs, and Load operations without FLS checks. - Use Case: You need a high-volume read-only list of open Cases for a FlexCard. The Skill selects Turbo Extract, generates the OmniDataTransform record with bounded filters, validates field mappings, and deploys it via the platform-metadata-deploy skill. ## Quick Start Ask the AI to create an Extract Data Mapper that pulls Account records with related Contacts for your target org and validate it before deployment.