database-design

# Database Design Skill

> **Purpose**: Atomic skill for database architecture with comprehensive parameter validation and optimization patterns.

## Skill Identity

| Attribute | Value |
|-----------|-------|
| **Scope** | Schema Design, Indexing, Query Optimization |
| **Responsibility** | Single: Data modeling and storage patterns |
| **Invocation** | `Skill("database-design")` |

## Parameter Schema

### Input Validation
```yaml
parameters:
  database_context:
    type: object
    required: true
    properties:
      use_case:
        type: string
        enum: [oltp, olap, htap, time_series, document, graph]
        required: true
      data_characteristics:
        type: object
        required: true
        properties:
          volume:
            type: string
            pattern: "^\\d+[KMGTP]B$"
          velocity:
            type: string
            pattern: "^\\d+[KM]?\\s*(reads?|writes?)/s$"
          variety:
            type: string
            enum: [structured, semi_structured, unstructured]
      access_patterns:
        type: array
        items:
          type: object
          properties:
            query_type: { type: string }
            frequency: { type: string, enum: [high, medium, low] }
            latency_sla: { type: string, pattern: "^\\d+ms$" }
      consistency:
        type: string
        enum: [strong, eventual, read_your_writes]
        default: strong

validation_rules:
  - name: "oltp_latency"
    rule: "use_case == 'oltp' implies latency_sla <= '100ms'"
    error: "OLTP workloads typically require <100ms latency"
  - name: "volume_velocity_match"
    rule: "high_volume implies adequate_velocity"
    error: "Volume and velocity constraints may be incompatible"
```

### Output Schema
```yaml
output:
  type: object
  properties:
    database_recommendation:
      type: object
      properties:
        primary: { type: string }
        secondary: { type: string }
        rationale: { type: string }
    schema:
      type: object