data-ml-readiness

What problem does it solve?

This Skill helps teams evaluate the readiness of data and machine learning systems by identifying risks related to contracts, lineage, reproducibility, privacy, and deployment reliability.

Core Features & Use Cases

• Risk Assessment: Evaluates data and ML project status to detect potential issues before deployment.
• Scope: Applicable when updating datasets, models, pipelines, or backend evaluation metrics, including privacy and lineage checks.
• Functionality: Analyzes data contracts, schema compatibility, reproducibility, model metrics, drift, and fallback strategies to ensure quality and safety.

Quick Start

Review the data and ML changes by providing details of the datasets, models, and pipelines affected.