Component Identification Sizing

Component Identification and Sizing

Overview

This public intake copy packages packages/skills-catalog/skills/(architecture)/component-identification-sizing from https://github.com/tech-leads-club/agent-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

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.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: How to Use, Core Concepts, Output Format, Component Inventory, Size Analysis Summary, Component Size Distribution.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• 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

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Map directory/namespace structure
2. For Node.js: services/, routes/, models/, utils/
3. For Java: Package structure (e.g., com.company.domain.service)
4. For Python: Module paths (e.g., app/billing/payment)
5. Identify leaf nodes
6. Components are the deepest directories containing source files
7. Example: services/BillingService/ is a component

Imported Workflow Notes

Imported: 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

Imported: 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

Imported: 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

Examples

Example 1: Ask for the upstream workflow directly

Use @component-identification-sizing to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @component-identification-sizing against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @component-identification-sizing for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @component-identification-sizing using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• 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't count test files in component size

Imported Operating Notes

Imported: 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

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in packages/skills-catalog/skills/(architecture)/component-identification-sizing, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @accessibility - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @ai-cold-outreach - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @ai-pricing - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @ai-sdr - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

• QUICK-REFERENCE.md
• README.md

Imported Reference Notes

Imported: 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

Imported: Output Format

Component Inventory Table

#### Imported: 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

#### Imported: 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

#### Imported: 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

#### Imported: 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.

Imported: 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

Imported: 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

Imported: 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',
    }))
}

Imported: 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