ai-factory.verify

To verify code implementation against a project plan, run an audit that checks task completion, build status, and test results. This process identifies any code-to-plan drift and ensures all requirements are fully addressed before deployment.

Code-to-plan drift occurs when implemented features deviate from the original project requirements. You can check for drift by auditing task completion against plan files and reviewing git history to identify missing tasks or leftover artifacts.

Run a quality gate check by assessing build status, test results, and linting on the new code. This confirms the implementation compiles correctly, passes all tests, and leaves no remaining TODOs or configuration issues.

Yes, plan adherence verification requires access to git history, plan files, and build or test tooling. These inputs are necessary to accurately audit task completion, confirm requirements are met, and identify deviations.

The best way to audit completed tasks for leftover artifacts is to perform a consistency check that compares the project plan against the final codebase. This identifies configuration issues, unaddressed tasks, and lingering temporary files.