What problem does it solve?
This Skill solves the common domain-driven design challenge of ambiguous domain terminology, premature generalization leading to unmaintainable "God classes", and unnecessary splitting of bounded contexts that create avoidable complexity. It eliminates guesswork when deciding whether similar domain concepts can be safely unified or must remain separate in different contexts.
Core Features & Use Cases
- Bidirectional linguistic analysis: Detects both ambiguities (same word meaning different things in different contexts) and generalization candidates (different words behaving identically in a specific context) to identify where contexts should split or merge.
- Dual operation modes: Supports full domain distillation for end-to-end context mapping, and single concept probe mode for iterative analysis of individual suspected generalizations.
- Safety guardrails: Includes fit tests to avoid unnecessary use, deep effect testing to prevent shallow generalization mistakes, and explicit boundary validation to avoid context leakage.
- Use case example: For a training management domain with rooms, trainers, and equipment all requiring reservation, the Skill identifies that they can be generalized to a ReservableResource abstraction in the scheduling context, while keeping their specific models in HR (for trainer vacation) and maintenance (for equipment service) contexts.
Quick Start
Provide your full domain description, event storming output, or a single concept you suspect can be generalized to the context-distiller skill to receive a distilled context map with identified ambiguities, shared abstractions, and bounded context boundaries.
