RDEWAI
Official@rdewai
Offers standardized engineering governance for medallion data pipelines, managing design documentation, sprint backlogs, and Spark-based infrastructure generation.
Agent Skills by RDEWAI
Showing 60 vetted skills indexed across 1 GitHub repositories.
RDEWAIcreate-dms
Generate compliant Data Model Specification documents from HLD and DRD inputs.
RDEWAIupdate-dms
Merge schema changes and SCD updates into DMS documents with versioning.
RDEWAIapply-learnings
Process pending user corrections from a learnings queue into generalized skill rules.
RDEWAIapprove-dms
Approve Data Model Specification documents by updating status and logging version history.
RDEWAIvalidate-dms
Validate DMS documents for completeness and quality standards.
RDEWAIupdate-stories
Updates sprint backlogs for data engineering projects when design artifacts, capacity, or priorities change.
RDEWAIcreate-stories
Decompose approved technical design artifacts into structured sprint backlogs for data engineering teams.
RDEWAIapprove-stories
Validate and update sprint backlogs to Approved status with metadata changes.
RDEWAIvalidate-stories
Validate sprint backlog completeness and quality before sprint planning.
RDEWAIvalidate-stm
Validate Source-to-Target Mapping Excel workbooks for completeness and quality.
RDEWAIcreate-stm
Generate standardized source-to-target mapping Excel workbooks for medallion data pipelines.
RDEWAIapprove-stm
Approve Source-to-Target Mapping Excel workbooks by updating their status.
RDEWAIupdate-stm
Update Source-to-Target Mapping Excel workbooks with schema changes and transformation rules.
RDEWAIvalidate-drd
Validate Data Requirements Documents for completeness and quality gaps.
RDEWAIupdate-drd
Merge new business requirements into Data Requirements Documents while preserving unchanged content.
RDEWAIapprove-drd
Approves Data Requirements Documents by updating status to Approved with validation checks and audit logging.
RDEWAIcreate-drd
Translate unstructured business inputs into formal Data Requirements Documents.
RDEWAIupdate-dqs
Updates DQS documents with new mappings, schemas, SLAs, and thresholds.
RDEWAIapprove-dqs
Approve Data Quality Specification documents by updating status and metadata.
RDEWAIcreate-dqs
Generate build-ready Data Quality Specifications from approved STM, DMS, and DRD artifacts for Spark-Expectations integration.
RDEWAIgenerate-se-rules
Convert DQS markdown documents into per-table Spark-Expectations YAML rule files.
RDEWAIvalidate-dqs
Validate Data Quality Specification documents for completeness and quality standards.
RDEWAIvalidate-hld
Validate data engineering HLD documents against completeness and quality standards.
RDEWAIapprove-hld
Approve high-level design documents by updating status and version history.
Frequently Asked Questions About RDEWAI
FAQPage SchemaWhat specific tasks does RDEWAI enable for data engineers?▼
RDEWAI enables the generation of formal Data Requirements Documents, Source-to-Target Mapping workbooks, and Low-Level Design specifications. It further supports the creation of Spark-based ingestion code, Apache Airflow DAGs, and CI/CD pipeline configurations while enforcing quality standards through automated validation gates.
Which personas benefit most from these capabilities?▼
Data engineers, technical architects, and project managers benefit from these capabilities. The system is designed for teams managing complex medallion data pipelines who require strict traceability between business requirements, technical design artifacts, and final production-ready code deployments.
What are the prerequisites for generating data pipeline artifacts?▼
Generation requires approved upstream artifacts, specifically Data Requirements Documents (DRD) and Source-to-Target Mapping (STM) workbooks. These documents serve as the source of truth for generating downstream Low-Level Designs, Spark-Expectations YAML rules, and project scaffold files.