/lightweight-design-analysis

Lightweight Design Analysis

A Claude Code skill for rigorous, evidence-based code design analysis across 8 quality dimensions

What It Does

Analyzes code at the class or module level to identify design improvement opportunities across:

1. Naming - Intention-revealing names, domain terminology, avoiding generic words
2. Object Calisthenics - Especially indentation levels, small methods, single responsibility
3. Coupling & Cohesion - Feature envy, inappropriate intimacy, grouping related concepts
4. Immutability - Const by default, readonly properties, pure functions
5. Domain Integrity - Rich domain models, avoiding anemic entities, encapsulation
6. Type System - Making illegal states unrepresentable, avoiding any/as
7. Simplicity - Removing duplication, dead code, over-engineering
8. Performance - Algorithmic efficiency (only evidence-based, not premature optimization)

When to Use

Invoke this skill when you want to:

• Analyze code quality before or after implementation
• Find refactoring opportunities in existing code
• Review design of a class or module
• Identify anti-patterns like anemic domain models or feature envy
• Assess type safety and domain modeling

Perfect for: The 🔵 REFACTOR phase of TDD workflow

How It Works

1. Understands First - Auto-invokes lightweight-implementation-analysis-protocol to comprehend code flow
2. Systematic Evaluation - Analyzes all 8 dimensions with specific, evidence-based criteria
3. Structured Report - Provides findings with severity levels (🔴 Critical, 🟡 Suggestion)
4. Actionable Recommendations - Shows before/after code examples with file:line references

Philosophy

This skill embodies principles from:

• Type-Driven Development (Scott Wlaschin) - Use types to express domain concepts
• Domain-Driven Design (Eric Evans) - Rich domain models with encapsulated behavior
• Object Calisthenics (Jeff Bay) - Strict coding constraints that enforce good design
• Clean Code (Robert C. Martin) - Intention-revealing names, single responsibility
• Working Effectively with Legacy Code (Michael Feathers) - Identifying improvement opportunities

Example Usage

User: "Analyze the Order class for design improvements"

Claude: [Auto-invokes implementation-analysis to understand Order.ts]

Claude: [Generates design analysis report]

# Design Analysis Report

**Analyzed:** Order.ts
**Lines Reviewed:** 1-85

## Summary
- Anemic domain model detected: Order has no business logic
- Feature envy: OrderService accesses many Order properties

## 🔴 Critical Issues

### Domain Integrity - Anemic Domain Model
**Location:** Order.ts:1-30
**Issue:** Order class only stores data, no business behavior
**Impact:** Business logic scattered across services, hard to maintain
**Recommendation:** Move calculateTotal() and validateItems() into Order

[Code examples...]

## 🟡 Suggestions

### Object Calisthenics - Indentation
**Location:** Order.ts:42-58
**Issue:** Method has 3 levels of nesting
**Recommendation:** Extract nested logic to separate methods

[Code examples...]

## Metrics
- Dimensions Evaluated: 8/8
- Critical Issues: 1
- Suggestions: 2

Output Format

Every finding includes:

• Severity Level: 🔴 Critical | 🟡 Suggestion
• Dimension: Which of the 8 dimensions
• Location: Exact file:line reference
• Issue: What's wrong (evidence-based)
• Impact: Why it matters
• Recommendation: Specific, actionable fix
• Code Example: Before/after snippets

Integration

• Auto-invokes lightweight-implementation-analysis-protocol to understand code first
• Complements your TDD workflow during refactoring phases
• Iterative - Run again after applying improvements to measure progress

Key Principles

✅ Evidence-Based - Every finding has file:line reference and code example ✅ Specific, Not Generic - Explicit detection criteria (2.54x more effective) ✅ Systematic - Evaluates all 8 dimensions, nothing missed ✅ Actionable - Shows exact code improvements, not abstract suggestions ✅ Rigorous - No speculation ("probably", "maybe"), only verified findings ✅ Focused - Only highlights issues and improvements, no noise

❌ Never Guesses - Understands code flow first via implementation-analysis ❌ Not Execution - Provides analysis and recommendations, doesn't implement ❌ Not Nitpicky - Skips trivial style preferences, focuses on design ❌ Not Premature - Only flags performance issues with evidence of inefficiency

Version History

• v1.0.0 - Initial release with 8 core dimensions

Contributing

This is a living skill that evolves based on what works. After using it, consider:

• Adding new dimensions if gaps are discovered
• Refining criteria if false positives occur
• Updating examples with real-world findings
• Adjusting severity thresholds based on experience

Author

Created for iterative, evidence-based code design improvement.