code-coupling-analysis

# Coupling Analysis Skill

Analyze code coupling across three dimensions and generate actionable HTML reports.

## Framework: Balanced Coupling (Vlad Khononov)

Three key dimensions determine coupling risk:

### 1. Integration Strength (How tightly modules connect)
| Level | Score | Detection Pattern |
|-------|-------|-------------------|
| Intrusive | 1.00 | Direct property access, internal state manipulation |
| Functional | 0.75 | Function/component usage, hooks, methods |
| Model | 0.50 | Data type imports, interfaces used as data |
| Contract | 0.25 | Pure interface/type imports |

### 2. Distance (Where dependencies live)
| Level | Score | Detection Pattern |
|-------|-------|-------------------|
| Same Module | 0.25 | Same directory (`./Component`) |
| Sibling Module | 0.50 | Sibling directory (`../utils`) |
| Distant Module | 0.75 | Different top-level (`@/contexts`, `~/lib`) |
| External | 1.00 | External packages (`react`, `lodash`) |

### 3. Volatility (Change frequency from Git history)
| Level | Score | Changes (6 months) |
|-------|-------|-------------------|
| Low | 0.00 | 0-2 changes |
| Medium | 0.50 | 3-10 changes |
| High | 1.00 | 11+ changes |

### Balance Score Formula
```
balance = (strength × volatility) × 0.6 + |strength - (1 - distance)| × 0.4
```

**Interpretation:**
- 0.0 - 0.2: Well balanced (ideal)
- 0.2 - 0.4: Acceptable
- 0.4 - 0.6: Needs attention
- 0.6+: Risky, consider refactoring

## Execution Steps

### Step 1: Identify Target Directory and Language

Determine the primary language by checking for:
- `tsconfig.json` or `*.ts`/`*.tsx` → TypeScript
- `pyproject.toml` or `*.py` → Python
- `go.mod` or `*.go` → Go
- `Cargo.toml` or `*.rs` → Rust
- `package.json` with `*.js`/`*.jsx` → JavaScript

### Step 2: Gather File List

```bash
# TypeScript/JavaScript
find . -type f \( -name "*.ts" -o -name "*.tsx" -o -name "*.js" -o -name "*.jsx" \) \
  -not -path "*/node_modules/*" \
  -not -path "*/.git/*" \
  -not -name "*.d.ts" \
  -not -nam