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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 a subdomain

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))

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/BillingService      | 4,312      | 23    | 5%      | ✅ OK        |
| Reporting       | services/ReportingService    | 27,765     | 162   | 33%     | ⚠️ Too Large |
| Notification    | services/NotificationService | 1,433      | 7     | 2%      | ✅ OK        |

Status Legend :

• ✅ OK: Well-sized (within 1-2 std dev from mean)
• ⚠️ Too Large: Exceeds size threshold or >2 std dev above mean
• 🔍 Too Small: <1% of codebase or <1 std dev below mean

Size Analysis Summary

## Size Analysis Summary

**Total Components**: 18
**Total Statements**: 82,931
**Mean Component Size**: 4,607 statements
**Standard Deviation**: 5,234 statements

**Oversized Components** (>2 std dev or >10%):

- Reporting (33% - 27,765 statements) - Consider splitting into:
  - Ticket Reports
  - Expert Reports
  - Financial Reports

**Well-Sized Components** (within 1-2 std dev):

- Billing Payment (5%)
- Customer Profile (5%)
- Ticket Assignment (9%)

**Undersized Components** (<1 std dev):

- Login (2% - 1,865 statements) - Consider consolidating with Authentication

Component Size Distribution

## Component Size Distribution

Component Size Distribution (by percent of codebase)

[Visual representation or histogram if possible]

Largest: ████████████████████████████████████ 33% (Reporting) ████████ 9% (Ticket Assign) ██████ 8% (Ticket) ██████ 6% (Expert Profile) █████ 5% (Billing Payment) ████ 4% (Billing History) ...

### Recommendations

```markdown
## Recommendations

### High Priority: Split Large Components

**Reporting Component** (33% of codebase):
- **Current**: Single component with 27,765 statements
- **Issue**: Too large, contains multiple functional areas
- **Recommendation**: Split into:
  1. Reporting Shared (common utilities)
  2. Ticket Reports (ticket-related reports)
  3. Expert Reports (expert-related reports)
  4. Financial Reports (financial reports)
- **Expected Result**: Each component ~7-9% of codebase

### Medium Priority: Review Small Components

**Login Component** (2% of codebase):
- **Current**: 1,865 statements, 3 files
- **Consideration**: May be too granular if related to broader authentication
- **Recommendation**: Evaluate if should be consolidated with Authentication/User components

### Low Priority: Monitor Well-Sized Components

Most components are appropriately sized. Continue monitoring during decomposition.

Analysis Checklist

Component Identification :

• Mapped all directory/namespace structures
• Identified leaf nodes (components) vs parent nodes (subdomains)
• Created complete component inventory
• Documented namespace/path for each component

Size Calculation :

• Counted statements (not lines) for each component
• Counted source files (excluding tests/configs)
• Calculated percentage of total codebase
• Calculated mean and standard deviation

Size Assessment :

• Identified oversized components (>threshold or >2 std dev)
• Identified undersized components (<1% or <1 std dev)
• Flagged components for splitting or consolidation
• Documented size distribution

Recommendations :

• Suggested splits for oversized components
• Suggested consolidations for undersized components
• Prioritized recommendations by impact
• Created architecture stories for refactoring

Implementation Notes

For Node.js/Express Applications

Components typically found in:

• services/ - Business logic components
• routes/ - API endpoint components
• models/ - Data model components
• utils/ - Utility components
• middleware/ - Middleware components

Example Component Identification :

services/
├── BillingService/          ← Component (leaf node)
│   ├── index.js
│   └── BillingService.js
├── CustomerService/          ← Component (leaf node)
│   └── CustomerService.js
└── NotificationService/      ← Component (leaf node)
    └── NotificationService.js

For Java Applications

Components identified by package structure:

• com.company.domain.service - Service components
• com.company.domain.model - Model components
• com.company.domain.repository - Repository components

Example Component Identification :

com.company.billing.payment   ← Component (leaf package)
com.company.billing.history   ← Component (leaf package)
com.company.billing           ← Subdomain (parent of payment/history)

Statement Counting

JavaScript/TypeScript :

• Count statements terminated by ; or newline
• Include: assignments, function calls, returns, conditionals, loops
• Exclude: comments, blank lines, declarations without assignment

Java :

• Count statements terminated by ;
• Include: method calls, assignments, returns, conditionals
• Exclude: class/interface declarations, comments, blank lines

Python :

• Count executable statements (not comments or blank lines)
• Include: assignments, function calls, returns, conditionals
• Exclude: docstrings, comments, blank lines

Fitness Functions

After identifying and sizing components, create automated checks:

Component Size Threshold

// Alert if any component exceeds 10% of codebase
function checkComponentSize(components, threshold = 0.1) {
  const totalStatements = components.reduce((sum, c) => sum + c.statements, 0)
  return components
    .filter((c) => c.statements / totalStatements > threshold)
    .map((c) => ({
      component: c.name,
      percent: ((c.statements / totalStatements) * 100).toFixed(1),
      issue: 'Exceeds size threshold',
    }))
}

Standard Deviation Check

// Alert if component is >2 standard deviations from mean
function checkStandardDeviation(components) {
  const sizes = components.map((c) => c.statements)
  const mean = sizes.reduce((a, b) => a + b, 0) / sizes.length
  const stdDev = Math.sqrt(sizes.reduce((sum, size) => sum + Math.pow(size - mean, 2), 0) / (sizes.length - 1))

  return components
    .filter((c) => Math.abs(c.statements - mean) > 2 * stdDev)
    .map((c) => ({
      component: c.name,
      deviation: ((c.statements - mean) / stdDev).toFixed(2),
      issue: 'More than 2 standard deviations from mean',
    }))
}

Best Practices

Do's ✅

• Use statements, not lines of code
• Identify components as leaf nodes only
• Calculate both percentage and standard deviation
• Consider application size when setting thresholds
• Document namespace/path for each component
• Create visual size distribution if possible

Don'ts ❌

• Don't count test files in component size
• Don't treat parent directories as components
• Don't use fixed thresholds without considering app size
• Don't ignore small components (may need consolidation)
• Don't skip standard deviation calculation
• Don't mix infrastructure and domain components in same analysis

Next Steps

After completing component identification and sizing:

1. Apply Gather Common Domain Components Pattern - Identify duplicate functionality
2. Apply Flatten Components Pattern - Remove orphaned classes from root namespaces
3. Apply Determine Component Dependencies Pattern - Analyze coupling between components
4. Create Component Domains - Group components into logical domains

Notes

• Component size thresholds vary by application size
• Small apps (<10 components): 30% threshold may be appropriate
• Large apps (>20 components): 10% threshold is more appropriate
• Standard deviation is more reliable than fixed percentages
• Well-sized components are 1-2 standard deviations from mean
• Oversized components often contain multiple functional areas that can be split

Weekly Installs

60

Repository

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GitHub Stars

2.0K

First Seen

Feb 7, 2026

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