AI-Oriented Source Code Aggregation and Minimization in Python Projects: Design and Implementation of a Developer Utility

Modern software development increasingly relies on large language models for code review,debugging, documentation, and architectural analysis. Large codebases introduce challengesrelated to size limits, noise, and irrelevant content. This paper presents an applied Python-basedutility that scans project directories, filters relevant files, minimizes source code, and packages it inan AI-friendly structured format using static analysis and language-aware processing.