aif-improve

You refine an AI-generated implementation plan by re-analyzing the codebase to identify gaps, missing tasks, and incorrect dependencies. This deeper code exploration updates the plan file with corrected task ordering and necessary steps.

Implementation plan refinement is the process of scanning a codebase to detect overlooked details and improve plan quality. It enhances existing plans by identifying integration points and analyzing edge cases before implementation begins.

Yes, codebase analysis detects incorrect dependencies and missing tasks within existing implementation plans. It refines task descriptions and corrects task ordering by exploring the codebase for overlooked integration points.

You need codebase re-analysis for edge case identification after generating an initial implementation plan. It ensures the plan is robust, accounts for existing code patterns, and covers all necessary edge cases.

The best way to improve plan quality is performing deeper code exploration to find gaps and refine task descriptions. This approach updates the plan file to reflect approved changes and ensures correct task ordering.

Yes, plan refinement supports user-prompted improvements and updates the plan file to reflect approved changes. It re-analyzes the codebase to enhance plan completeness and correct incorrect dependencies.