What problem does it solve? Code reviews often miss recurring structural problems like god objects, N+1 queries, flaky tests, and hardcoded secrets because reviewers lack a systematic detection framework. This Skill provides categorized anti-pattern checklists with severity levels and concrete refactoring steps so findings are consistent and actionable. ## Core Features & Use Cases - Systematic Detection Checklists: Covers design/OOP, code smells, architecture, database, testing, and security anti-patterns, each with severity ratings from Low to Critical. - Refactoring Guidance: Provides before/after code examples for common fixes such as extracting methods, guard clauses, eager loading for N+1 queries, and dependency inversion for circular dependencies. - Language-Specific Resources: Includes dedicated anti-pattern references for JavaScript, Python, Go, and Ruby. - Use Case: During a pull request review, apply the quick review checklist to flag a 1,200-line controller as a God Object (High severity), detect SQL string concatenation (Critical), and document both with suggested NFRs for a technical debt register. ## Quick Start Ask the AI to review a source file or module using the anti-pattern-analysis checklists and report each finding with its severity level and a suggested refactoring approach.
