/component-identification-sizing

name: component-identification-sizing
description: Maps architectural components in a codebase and measures their size to identify what should be extracted first. Use when asking "how big is each module?", "what components do I have?", "which service is too large?", "analyze codebase structure", "size my monolith", or planning where to start decomposing. Do NOT use for runtime performance sizing or infrastructure capacity planning.

Component Identification and Sizing

This skill identifies architectural components (logical building blocks) in a codebase and calculates size metrics to assess decomposition feasibility and identify oversized components.

How to Use

Quick Start

Request analysis of your codebase:

• **"Identify and size all components in this codebase"**
• **"Find oversized components that need splitting"**
• **"Create a component inventory for decomposition planning"**
• **"Analyze component size distribution"**

Usage Examples

**Example 1: Complete Analysis**

User: "Identify and size all components in this codebase"

The skill will:
1. Map directory/namespace structures
2. Identify all components (leaf nodes)
3. Calculate size metrics (statements, files, percentages)
4. Generate component inventory table
5. Flag oversized/undersized components
6. Provide recommendations

**Example 2: Find Oversized Components**

User: "Which components are too large?"

The skill will:
1. Calculate mean and standard deviation
2. Identify components >2 std dev or >10% threshold
3. Analyze functional areas within large components
4. Suggest specific splits with estimated sizes

**Example 3: Component Size Analysis**

User: "Analyze component sizes and distribution"

The skill will:
1. Calculate all size metrics
2. Generate size distribution summary
3. Identify outliers
4. Provide statistics and recommendations

Step-by-Step Process

1. **Initial Analysis**: Start with complete component inventory 2. **Identify Issues**: Find components that need attention 3. **Get Recommendations**: Request actionable split/consolidation suggestions 4. **Monitor Progress**: Track component growth over time

When to Use

Apply this skill when:

• Starting a monolithic decomposition effort
• Assessing codebase structure and organization
• Identifying components that are too large or too small
• Creating component inventory for migration planning
• Analyzing code distribution across components
• Preparing for component-based decomposition patterns

Core Concepts

Component Definition

A **component** is an architectural building block that:

• Has a well-defined role and responsibility
• Is identified by a namespace, package structure, or directory path
• Contains source code files (classes, functions, modules) grouped together
• Performs specific business or infrastructure functionality

**Key Rule**: Components are identified by **leaf nodes** in directory/namespace structures. If a namespace is extended (e.g., `services/billing` extended to `services/billing/payment`), the parent becomes a **subdomain**, not a component.

Size Metrics

**Statements** (not lines of code):

• Count executable statements terminated by semicolons or newlines
• More accurate than lines of code for size comparison
• Accounts for code complexity, not formatting

**Component Size Indicators**:

• **Percent of codebase**: Component statements / Total statements
• **File count**: Number of source files in component
• **Standard deviation**: Distance from mean component size

Analysis Process

Phase 1: Identify Components

Scan the codebase directory structure:

1. **Map directory/namespace structure**

• For Node.js: `services/`, `routes/`, `models/`, `utils/`
• For Java: Package structure (e.g., `com.company.domain.service`)
• For Python: Module paths (e.g., `app/billing/payment`)

2. **Identify leaf nodes**

• Components are the deepest directories containing source files
• Example: `services/BillingService/` is a component
• Example: `services/BillingService/payment/` extends it, making `BillingService` a subdomain

3. **Create component inventory**

• List each component with its namespace/path
• Note any parent namespaces (subdomains)

Phase 2: Calculate Size Metrics

For each component:

1. **Count statements**

• Parse source files in component directory
• Count executable statements (not comments, blank lines, or declarations alone)
• Sum across all files in component

2. **Count files**

• Total source files (`.js`, `.ts`, `.java`, `.py`, etc.)
• Exclude test files, config files, documentation

3. **Calculate percentage**

   component_percent = (component_statements / total_statements) * 100

4. **Calculate statistics**

• Mean component size: `total_statements / number_of_components`
• Standard deviation: `sqrt(sum((size - mean)^2) / (n - 1))`
• Component's deviation: `(component_size - mean) / std_dev`

Phase 3: Identify Size Issues

**Oversized Components** (candidates for splitting):

• Exceeds 30% of total codebase (for small apps with <10 components)
• Exceeds 10% of total codebase (for large apps with >20 components)
• More than 2 standard deviations above mean
• Contains multiple distinct functional areas

**Undersized Components** (candidates for consolidation):

• Less than 1% of codebase (may be too granular)
• Less than 1 standard deviation below mean
• Contains only a few files with minimal functionality

**Well-Sized Components**:

• Between 1-2 standard deviations from mean
• Represents a single, cohesive functional area
• Appropriate percentage for application size

Output Format

Component Inventory Table

## Component Inventory

| Component Name  | Namespace/Path               | Statements | Files | Percent | Status       |
| --------------- | ---------------------------- | ---------- | ----- | ------- | ------------ |
| Billing Payment | services/Billin