clean-code-size

Identify oversized source files exceeding language-specific line thresholds.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/OntoLedgy/ol_ai_context_library --skill clean-code-size
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: clean-code-size
Source: https://github.com/OntoLedgy/ol_ai_context_library/tree/main/skills/clean-code-size
Command: npx skills add https://github.com/OntoLedgy/ol_ai_context_library --skill clean-code-size

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill eliminates the guesswork of maintaining monolithic codebases where oversized source files are hard to review, assign ownership for, and refactor safely, providing a clear, data-driven triage process for structural decomposition.

Core Features & Use Cases

  • Deterministic Language-Aware Scanning: Automatically detects file languages and applies appropriate size thresholds for Python, JavaScript/TypeScript, C#, Rust, and Go, with support for custom threshold overrides.
  • False Positive Filtering: Exempts legitimate large files like generated code, constant registries, test fixtures, and schema declarations to avoid unnecessary split proposals.
  • Architect-Led Split Planning: For files that require structural changes, generates a detailed module breakdown with defined responsibilities, dependency direction, and safe migration order, ready for implementation by downstream engineering skills.
  • Use Case: Use this when your repository feels monolithic, files have become too large to review effectively, or you need a size-focused triage step before running refactoring work or handing tasks to language-specific data engineers.

Quick Start

Ask the AI to scan your codebase for oversized source files and generate a proposed module split plan for any files that need structural decomposition.

Frequently Asked Questions about clean-code-size

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify oversized files in a monolithic codebase for refactoring?

To identify oversized files in a monolithic codebase for refactoring, scan the repository using language-specific non-blank line thresholds. This triage process flags large source files as candidates for structural decomposition and generates architect-led module split proposals.

What is the best way to plan safe module splits for large source files?

The best way to plan safe module splits for large source files is to generate an architect-led module breakdown. This defines specific module responsibilities, dependency directions, and a safe migration order, routing implementation to downstream engineering skills.

Does code size triage work with Python, JavaScript, TypeScript, and Go projects?

Code size triage works with Python, JavaScript, TypeScript, C#, Rust, and Go projects. It automatically detects file languages and applies appropriate size thresholds, with support for custom threshold overrides to accurately flag files for structural decomposition.

How are legitimate large files filtered during a code audit size triage?

During a code audit size triage, legitimate large files are filtered out using false positive filtering. This exempts generated code, constant registries, test fixtures, and schema declarations from receiving unnecessary module split proposals.

When should I run an architecture review for module decomposition?

You should run an architecture review for module decomposition when your repository feels monolithic and files become too large to review effectively. It serves as a size-focused triage step before running refactoring work or assigning tasks to language-specific engineers.