What problem does it solve? Code that merely passes tests often hides vague naming, accidental fixes, and drift from the business domain, making every future change slower and riskier. This Skill enforces disciplined implementation practices so code stays obvious, safe to refactor, and readable by domain experts. ## Core Features & Use Cases - Precise Naming Discipline: Bans vague names like process, handle, and data in favor of names that signal purpose at the call site, such as calculateMonthlyRevenue. - Safe Refactoring Workflow: Requires a green test suite before every refactoring step, limits each step to 3-4 files, and mandates small incremental commits. - Domain-Aligned Code: Ensures business concepts (accounts, invoices, policies) appear as first-class terms in code so domain experts can read it. - Intentional Comments and Anti-Coincidence Checks: Comments capture intent, trade-offs, and assumptions rather than restating code, and every committed line must have a explainable reason for working. - Use Case: When refactoring a billing module, apply the checklist to rename generic functions to domain terms, verify tests pass after each small step, and replace redundant comments with design rationale referencing ADRs. ## Quick Start Ask the AI to review or write code using the implementation practice checklist, ensuring names signal purpose, tests stay green during refactoring, and comments explain intent rather than restating code.
