How do you implement agentic AI for automated code refactoring recommendation?
Code refactoring recommendation agents identify code quality issues and suggest specific improvements with implementation guidance. Configure agents with access to source code repositories, static analysis results, and code quality metrics. The agent identifies refactoring opportunities including long methods, large classes, duplicated code, complex conditionals, and inappropriate coupling. Generate specific refactoring recommendations with before-and-after code examples. Prioritize recommendations based on code change frequency, bug density, and developer pain points. Estimate refactoring effort for each recommendation. Implement safe refactoring verification that confirms behavioral equivalence after changes. Track refactoring impact on code quality metrics and defect rates. Support incremental refactoring plans that spread improvement work across multiple sprints.