verify-change

To analyze code changes and detect documentation gaps before a git commit, run an automated change analyzer script. It evaluates working changes, validates the scope, checks README.md and DESIGN.md synchronization, and outputs a structured report of affected modules and risks.

Code change impact assessment identifies how modifications affect existing modules to prevent integration risks. It is needed to map changes to affected components, detect potential issues early, and ensure codebase stability during software maintenance and branch merging.

To check if your README.md and DESIGN.md are synchronized with your code modifications, use an automated change analysis tool. It assesses documentation sync status across staged and committed changes, then provides actionable recommendations for improvement.

Yes, automated change analysis works with staged, committed, and working git changes. It operates across all three states to identify variations in code, tests, and configuration files, generating a comprehensive report of risk findings and recommended follow-up actions.

The best way to generate a structured report of code risks and affected modules is using an automated change analyzer. It reviews diff variations, assesses impact across your project, and outputs a concise document listing risk findings and follow-up actions for branch workflows.

You should not use automated code review for change analysis when you require deep semantic logic validation or complex runtime behavior testing. It primarily focuses on diff scope validation, documentation synchronization, and module impact mapping rather than functional execution.