Atlas / Skills / tech-leads-club / Component Identification Sizing

Component Identification SizingSAFE

skills/tech-leads-club/component-identification-sizing

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Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
NOASSERTION
Stars
7,038
01

Overview

From the repository's own README, as read at the audited commit. Badges and raw HTML are left out.

A skill for identifying architectural components in codebases and calculating size metrics to support decomposition planning and migration efforts.

What This Skill Does

This skill analyzes codebases to:

  1. Identify architectural components (logical building blocks) from directory/namespace structures
  2. Calculate size metrics using statements (not lines of code) for accurate comparison
  3. Detect oversized components that exceed thresholds or standard deviations
  4. Identify undersized components that may need consolidation
  5. Generate component inventory tables with size statistics
  6. Provide recommendations for splitting large components or consolidating small ones
  7. Assess decomposition feasibility based on component size distribution

When to Use This Skill

This skill is applied when you:

  • Ask to analyze codebase structure or organization
  • Request component identification or sizing analysis
  • Need help planning monolithic decomposition
  • Want to find oversized components that need splitting
  • Ask about architectural decomposition patterns
  • Request component inventory for migration planning
  • Discuss codebase metrics or statistics

Key Features

Language & Framework Agnostic

This skill works with any codebase in any language:

  • Node.js/Express: Analyzes services/, routes/, models/ directories
  • Java: Analyzes package structures (e.g., com.company.domain.service)
  • Python: Analyzes module paths (e.g., app/billing/payment)
  • C#/.NET: Analyzes namespace structures
  • Any language: Works with directory/namespace patterns

Accurate Size Metrics

Uses statements (not lines of code) for accurate size comparison:

  • Accounts for code complexity, not formatting
  • More reliable than line counts
  • Consistent across different coding styles
  • Standard deviation analysis for outlier detection

Actionable Output

Provides concrete, actionab

Read from source at commit 069343ba7895OBSERVED · 2026-10-07
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
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

```markdown
## Component Inventory

| Component Name  | Namespace/Path               | Statements | Files | Percent | Status       |
| --------------- | ---------------------------- | ---------- | ----- | ------- | ------------ |
| Billing Payment | services/Billin
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (1)

LOWInventory / provenance · inv.symlink · CWE-1104
CLAUDE.md
CLAUDE.md
Why it matters. link not followed

Gates applied: no_behavioural_pass.

Audited 2026-10-07 · audit v0.4.1 · source sha 069343ba7895full audit observations/trust-audit/skill/tech-leads-club__component-identification-sizing.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-07069343ba7895SAFEB89first audit
05

Questions

What does the Component Identification Sizing skill do?

The secure, validated skill registry for professional AI coding agents. Extend Antigravity, Claude Code, Cursor, Copilot and more with absolute confidence.

Is Component Identification Sizing safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Component Identification Sizing access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (069343ba7895), read on 2026-10-07. The repository is watched, and a new audit runs when it changes — this is the first audit.

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