What problem does it solve? Teams considering MetaObjects (the cross-language typed metadata standard) lack a rigorous way to decide whether adoption pays off. This Skill runs a read-only, pre-adoption assessment of a target repository and produces a decision-grade report covering fit, what would migrate, the end-state, and the drift-protection payoff — with every claim cited to file:line evidence. ## Core Features & Use Cases - Drift ledger with git archaeology: Hunts ten classes of drift exposure (duplicate validators, DTO mappers, opaque JSON columns, scattered prompts) and proves drift already happened via commit history. - Table-first census and reconciliation: Reconstructs the live table set from migrations, counts ORM classes, read models, and payload shapes, and predicts the future metadata spine size. - Fit rubric and migration waves: Works a disqualifier table row-by-row, then lays out parity-gated adoption waves from a zero-churn wedge to full spine ownership. - Use Case: Point an AI assistant at a TypeScript or Java repository that has not adopted MetaObjects; it emits metaobjects-fit/fit-assessment.md plus a machine-checkable JSON twin without modifying any code. ## Quick Start Ask the assistant to run a MetaObjects fit assessment on this repository and write the report to metaobjects-fit/fit-assessment.md.
