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component-identification-sizing

Identify leaf components and compute size metrics for decomposition planning.

1|Updated Feb 21, 2026
Search Tags:#architecture#codebase#components#decomposition#monolith#sizing#identify
One-click install
npx skills add https://github.com/marcius-llmus/skills --skill component-identification-sizing-marcius-llmus
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: component-identification-sizing
Source: https://github.com/marcius-llmus/skills/tree/main/%28architecture%29/component-identification-sizing
Command: npx skills add https://github.com/marcius-llmus/skills --skill component-identification-sizing-marcius-llmus

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the discovery of architectural components in a codebase and computes size metrics to guide decomposition planning, enabling teams to understand structure and identify candidates for splitting.

Core Features & Use Cases

  • Identify leaf components in directory/namespace structures
  • Calculate statements, files, and percentage metrics with standard deviation analysis
  • Generate a component inventory and actionable split/consolidation recommendations
  • Use for monolith decomposition, architecture reviews, and planning refactors

Quick Start

Request an analysis of a codebase to identify components and compute size metrics for planning decomposition.

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 monolith codebase?▼

You can identify components in a monolith codebase by analyzing directory and namespace structures to map leaf components, generating a detailed inventory for decomposition planning.

How do I calculate codebase size metrics for decomposition planning?▼

Codebase size metrics are calculated by computing statement and file counts per component, then applying percentage and standard deviation analysis to flag oversized components for splitting.

Can I analyze codebases written in Python, Java, or Node.js for component sizing?▼

Yes, component sizing analysis supports codebases written in Python, Java, Node.js, or any programming language, applying consistent statement counting and structural mapping across different environments.

What is the best way to find components to split during a monolith decomposition?▼

The best way to find components to split is to compute size metrics and standard deviations across your component inventory, which flags oversized components that require actionable splitting recommendations.

How does standard deviation analysis help with codebase refactoring?▼

Standard deviation analysis identifies size anomalies across mapped leaf components, highlighting outliers that significantly exceed average statement counts and providing actionable recommendations to split or consolidate them.

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