packages/skills-catalog/skills/(architecture)/component-identification-sizing/SKILL.md
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.
npx skillsauth add tech-leads-club/agent-skills component-identification-sizingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill identifies architectural components (logical building blocks) in a codebase and calculates size metrics to assess decomposition feasibility and identify oversized components.
Request analysis of your codebase:
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
Apply this skill when:
A component is an architectural building block that:
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.
Statements (not lines of code):
Component Size Indicators:
Scan the codebase directory structure:
Map directory/namespace structure
services/, routes/, models/, utils/com.company.domain.service)app/billing/payment)Identify leaf nodes
services/BillingService/ is a componentservices/BillingService/payment/ extends it, making BillingService a subdomainCreate component inventory
For each component:
Count statements
Count files
.js, .ts, .java, .py, etc.)Calculate percentage
component_percent = (component_statements / total_statements) * 100
Calculate statistics
total_statements / number_of_componentssqrt(sum((size - mean)^2) / (n - 1))(component_size - mean) / std_devOversized Components (candidates for splitting):
Undersized Components (candidates for consolidation):
Well-Sized Components:
## 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:
## 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 (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.
Component Identification:
Size Calculation:
Size Assessment:
Recommendations:
Components typically found in:
services/ - Business logic componentsroutes/ - API endpoint componentsmodels/ - Data model componentsutils/ - Utility componentsmiddleware/ - Middleware componentsExample Component Identification:
services/
├── BillingService/ ← Component (leaf node)
│ ├── index.js
│ └── BillingService.js
├── CustomerService/ ← Component (leaf node)
│ └── CustomerService.js
└── NotificationService/ ← Component (leaf node)
└── NotificationService.js
Components identified by package structure:
com.company.domain.service - Service componentscom.company.domain.model - Model componentscom.company.domain.repository - Repository componentsExample Component Identification:
com.company.billing.payment ← Component (leaf package)
com.company.billing.history ← Component (leaf package)
com.company.billing ← Subdomain (parent of payment/history)
JavaScript/TypeScript:
; or newlineJava:
;Python:
After identifying and sizing components, create automated checks:
// 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',
}))
}
// 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',
}))
}
After completing component identification and sizing:
tools
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development
Opinionated Rails conventions: rich models, concerns, CRUD-everything, state-as-records, minimal dependencies, Minitest with fixtures. Load this skill BEFORE any code-level thinking, not only before editing a file. It is required the moment a task touches Rails code in ANY way: designing or even just discussing a data model, schema, migration, entity, association, field, validation, class, or method name; writing, planning, reviewing, analyzing, testing, debugging, or refactoring; or proposing any model, table, column, route, or code snippet inline in chat. If you are about to name a model or sketch a column you are already in scope, even in an exploratory back-and-forth where no file is written yet. Do not let a "we're just discussing" framing defer it. Do NOT use for non-Rails backends, NestJS, or general architecture (use nestjs-modular-monolith or coding-guidelines).
testing
Feature planning and implementation with 4 adaptive phases — Specify, Design, Tasks, Execute. Auto-sizes depth by complexity. Creates atomic tasks with verification criteria, atomic git commits, and requirement traceability. Features an independent Verifier (author != verifier, evidence-or-zero), persistent decision log (STATE.md), and test-coverage-matrix-driven tests, plus a self-improving lessons layer that turns verification failures into reusable project-local guidance. Stack-agnostic. Use when (1) Planning features (requirements, design, task breakdown), (2) Implementing with verification and atomic commits, (3) Validating or verifying an implementation against a spec. Triggers on "specify feature", "discuss feature", "design", "tasks", "implement", "validate", "verify work", "UAT", "record decision", "pause work", "resume work". Do NOT use for architecture decomposition analysis (use architecture skills) or technical design docs (use create-technical-design-doc).
development
Generative Engine Optimization (GEO) specialist — the technical, on-page publishing work that makes a given page or site discoverable, understandable, trustworthy, quotable, and fresh for AI answer engines (Google AI Overviews, ChatGPT Search, Bing Copilot, Perplexity). Use when asked to 'optimize this page/site for GEO', 'optimize for AI search / answer engines', 'get my page cited by ChatGPT/Perplexity', 'improve AI visibility/citability', 'write an llms.txt', 'add citation-ready structure or schema for AI answers', 'otimizar para busca com IA', or to audit/create/improve a codebase for generative search. Do NOT use for AI-driven SEO content strategy or programmatic pages at scale (use ai-seo), classic keyword/SERP ranking (use seo), accessibility (use web-accessibility), or multi-area site audits (use web-quality-audit).