What problem does it solve? Before writing code, teams need confidence that their spec, design, tasks, and data model agree with each other. This Skill performs a pre-implementation quality check that detects inconsistencies across change artifacts and produces a go/no-go readiness verdict. ## Core Features & Use Cases - SSOT-Driven Consistency Checks: Cross-checks spec-model.yaml, design.md, spec.md, tasks.md, and questions.md against a selectable single source of truth, with a concrete fix suggestion for every issue found. - Readiness Report: Counts unresolved questions and assumptions, classifies acceptance criteria coverage, and optionally runs documentation coverage via the modscape CLI. - Clear Verdicts: Outputs a structured report ending in one of three verdicts: ready to implement, review warnings, or blocking issues. - Use Case: After drafting a design for a new data model change, run the check against spec-model.yaml to confirm every table is classified, every impacted table has tasks, and every open question has an assumption before implementation begins. ## Quick Start Ask the AI to run a spec check on your current change, for example by saying: run modscape-spec-check on my change using spec-model.yaml as the source of truth.
