What problem does it solve? Domain terminology drifts and design decisions get forgotten as a codebase grows, leaving future readers guessing why things were built a certain way. This Skill actively sharpens a project's domain model by challenging fuzzy terms, stress-testing concepts with concrete scenarios, and recording glossaries and decisions the moment they crystallize. ## Core Features & Use Cases - Ubiquitous Language Management: Maintains an opinionated CONTEXT.md glossary with canonical terms and explicit _Avoid_ synonyms, supporting both single-context repos and multi-context setups via CONTEXT-MAP.md. - Architecture Decision Records: Creates sequentially numbered ADRs in docs/adr/ only when a decision is hard to reverse, surprising without context, and the result of a real trade-off. - Live Model Sharpening: Challenges terms that conflict with the glossary, cross-references claims against actual code, and updates files inline rather than batching changes. - Use Case: While designing a billing feature, the user says "account" ambiguously; the Skill asks whether they mean Customer or User, resolves the term, updates CONTEXT.md immediately, and offers an ADR when the team picks event-based communication between Ordering and Billing contexts. ## Quick Start Ask the AI to help define the domain language for a new feature and record any significant architectural decisions as ADRs.
