component-identification-sizing

Identifies and measures codebase components by namespace and file counts.

Updated Feb 14, 2026
One-click install
npx skills add https://github.com/P4rzi/PROT-RISK --skill component-identification-sizing-p4rzi
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: component-identification-sizing
Source: https://github.com/P4rzi/PROT-RISK/tree/main/.github/skills/component-identification-sizing
Command: npx skills add https://github.com/P4rzi/PROT-RISK --skill component-identification-sizing-p4rzi

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill helps developers understand the structure and size of their codebase by identifying individual components and measuring their complexity, which is crucial for planning refactoring and decomposition efforts.

Core Features & Use Cases

  • Component Identification: Automatically maps directory and namespace structures to identify distinct architectural components (leaf nodes).
  • Size Metrics: Calculates component size using executable statements, file counts, and percentage of the total codebase.
  • Oversized/Undersized Detection: Flags components that are too large (potential candidates for splitting) or too small (potential candidates for consolidation).
  • Use Case: When planning to break down a large monolith, this skill provides a clear inventory of components, their sizes, and actionable recommendations on which ones to tackle first.

Quick Start

Use the component identification and sizing skill to identify and size all components in the current codebase.

Frequently Asked Questions about component-identification-sizing

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

FAQPage Schema
How do I identify architectural components in a monolithic codebase for decomposition?

Component identification analyzes directory and namespace structures to map distinct architectural components within a codebase. It detects leaf nodes by examining structural boundaries, providing a clear inventory of modules to support monolith decomposition and refactoring planning.

How do I measure component size to find oversized modules for refactoring?

Component size measurement calculates executable statements, file counts, and total codebase percentages. This skill flags oversized modules as split candidates and undersized components for consolidation, generating actionable metrics to guide refactoring and codebase analysis.

Does codebase component sizing work with Node.js, Java, and Python projects?

Codebase component sizing supports Node.js, Java, and Python projects. The analysis adapts to the specific directory and namespace conventions of these environments to accurately identify architectural components and calculate size metrics.

What is the best way to plan monolith decomposition using size metrics?

Planning monolith decomposition uses size metrics to prioritize which oversized components to tackle first. By calculating executable statements and file counts, this skill provides actionable recommendations for splitting large modules to guide your refactoring strategy.

When should I consolidate undersized components during codebase analysis?

Consolidating undersized components is recommended when codebase analysis flags modules as too small based on file counts and executable statements. This identification helps optimize software architecture by merging fragmented components during refactoring efforts.