ml-model-deployment

This skill designs dimensional models and fact tables for data warehouse projects. It clarifies requirements, reviews system constraints, and selects appropriate architectural patterns. The outputs include implementation plans, specifications, and validation steps for developers.

The data-catalog-creator skill helps developers design and plan systems for managing metadata, data lineage, and discovery. It generates implementation plans, architectural specs, and required artifacts based on your stack and constraints. Use this skill when you need to establish or improve data governance, compliance, and discoverability within your infrastructure.

The data-pipeline-builder skill designs and plans orchestration pipelines with a focus on idempotency. It's used when you need to create data workflows, producing artifacts like specs, configs, and validation steps. Developers should use it after confirming requirements and necessary approvals.

This skill helps developers implement data quality checks through validation, profiling, and anomaly detection. Use it when you need to design or plan a data quality system within a given architecture and stack. It guides you from clarifying requirements to producing implementation artifacts and acceptance criteria.