data-model-creation

Optional advanced tool for complex data modeling. For simple table creation, use relational-database-tool directly with SQL statements.

## When to use this skill

This is an **OPTIONAL advanced modeling tool** for complex database design. Most simple table creation should use `relational-database-tool` directly with SQL statements.

**ONLY use this skill when you specifically need:**
- Complex multi-table relationships with automatic foreign key management
- Visual ER diagram generation for documentation
- Automated field type mapping and constraint generation
- Enterprise-level data model documentation

**For most cases, use `relational-database-tool` skill instead:**
- Simple table creation with CREATE TABLE statements
- Basic CRUD operations
- Schema modifications with ALTER TABLE
- Direct SQL execution without Mermaid modeling

**Do NOT use for:**
- Querying or manipulating existing data (use database skills)
- NoSQL database design (use NoSQL skills)
- Frontend data structures (use appropriate frontend skills)

---

## How to use this skill (for a coding agent)

**⚠️ NOTE: This is OPTIONAL. For simple tasks, skip this and use `relational-database-tool` directly.**

When you do use this advanced modeling approach:

1. **Optional modeling workflow** (only when complexity justifies it)
   - Business analysis phase: Analyze user requirements, identify core entities and relationships
   - Mermaid modeling phase: Create mermaid classDiagram following generation rules
   - Model validation phase: Check completeness, consistency, and correctness

2. **Apply generation rules strictly** (when using this tool)
   - Use correct type mappings (string, number, boolean, x-enum, etc.)
   - Convert Chinese to English naming (PascalCase for classes, camelCase for fields)
   - Define required(), unique(), display_field() functions when needed
   - Use proper relationship notation with field names

3. **Use tools correctly** (only when you choose this approach)
   - Call data model creation tools only for complex multi-entity business requirements
   - Use `mermaidDiagram` parameter with complete mermaid classDiagram code
   - Set `publish` to false initially, create then publish separately
   - Choose appropriate `updateMode` for new or existing models

---

## Quick Decision Guide

**Most Database Tasks → `relational-database-tool` skill**
- ✅ Simple table creation
- ✅ Data queries and modifications
- ✅ Schema changes
- ✅ Direct SQL execution

**Complex Modeling Only → This skill (`data-model-creation`)**
- 🎯 Multi-entity relationship modeling
- 🎯 Automated foreign key management
- 🎯 Visual ER diagram generation
- 🎯 Enterprise documentation

---

# Data Model AI Modeling Professional Rules

## ⚠️ IMPORTANT: Simplified Workflow Recommendation

**For most database table creation tasks, use `relational-database-tool` skill directly:**

- Simple table creation: `CREATE TABLE users (id INT PRIMARY KEY, name VARCHAR(255))`
- Schema modifications: `ALTER TABLE users ADD COLUMN email VARCHAR(255)`
- Data operations: `INSERT`, `UPDATE`, `SELECT`, `DELETE`

**Only use this advanced Mermaid modeling approach when:**
- You need automated relationship management
- Complex multi-table schemas with foreign keys
- Enterprise documentation requirements
- Visual ER diagram generation

**This rule exists for complex modeling scenarios, but most development should use direct SQL execution.**

## AI Modeling Expert Prompt

As an expert in data modeling and a senior architect in software development, you are proficient in Mermaid. Your main task is to provide model structures in mermaid classDiagram format based on user descriptions, following the detailed rules below:

### Generation Rules

1. **Type Mapping Priority**: When user-described fields match the mapping relationship, prioritize using type as the field type. Mapping relationships are as follows:
   | Business Field | type |
   | --- | --- |
   | Text | string |
   | Number | number |
   | Boolean | boolean |
   | Enum | x-enum |
   | Email | email |
   | Phone | phone |
   | URL | url |
   | File | x-file |
   | Image | x-image |
   | Rich Text | x-rtf |
   | Region | x-area-code |
   | Time | time |
   | Date | date |
   | DateTime | datetime |
   | Object | object |
   | Array | string[] |
   | Location | x-location |

2. **Naming Convention**: Convert Chinese descriptions to English naming (except enum values). Use PascalCase for class names, camelCase for field names.

3. **Field Visibility**: Use default visibility for fields, do not add "+" or "-".

4. **Array Types**: When descriptions include array types, use specific array formats such as string[], number[], x-rtf[], etc.

5. **Chinese Administrative Regions**: When involving Chinese administrative regions like "province/city/district", use x-area-code field type.

6. **Required Fields**: When descriptions explicitly mention required fields, define a required() parameterless function, return value as string array of required field names, e.g., `required() ["name", "age"]`. By default, fields are not required.

7. **Unique Fields**: When descriptions explicitly mention unique fields, define a unique() parameterless function, return value as string array of unique field names, e.g., `unique() ["name", "age"]`. By default, fields are not unique.

8. **Default Values**: When descriptions explicitly require field default values, use "= default value" format after field definition, e.g., `age: number = 0`. By default, fields have no default values.

9. **Field Descriptions**: For each field definition in user descriptions, use `<<description>>` format at the end of the definition line, e.g., `name: string <<Name>>`.

10. **Display Field**: Each entity class should have a field for display when being referenced. Usually a human-readable name or unique identifier. Define display_field() parameterless function, return value is a field name representing the main display field, e.g., `display_field() "name"` means the main display field is name. Otherwise, default to the implicit _id of the data model.

11. **Class Notes**: After all class definitions are complete, use note to describe class names. First use "%% Class naming" to anchor the area, then provide Chinese table names for each class.

12. **Relationships**: When descriptions contain relationships, relationship label LabelText should not use original semantics, but use relationship field names. For example, `A "n" <-- "1" B: field1` means A has many-to-one relationship with B, data exists in A's field1 field. Refer to examples for specifics.

13. **Naming**: Field names and descriptions in Mermaid should be concise and accurately expressed.

14. **Complexity Control**: Unless user requires, control complexity, e.g., number of classes should not exceed 5, control field complexity.

### Standard Example

```mermaid
classDiagram
    class Student {
        name: string <<Name>>
        age: number = 18 <<Age>>
        gender: x-enum = "Male" <<Gender>>
        classId: string <<Class ID>>
        identityId: string <<Identity ID>>
        course: Course[] <<Courses>>
        required() ["name"]
        unique() ["name"]
        enum_gender() ["Male", "Female"]
        display_field() "name"
    }
    class Class {
        className: string <<Class Name>>
        display_field() "className"
    }
    class Course {
        name: string <<Course Name>>
        students: Student[] <<Students>>
        display_field() "name"
    }
    class Identity {
        number: string <<ID Number>>
        display_field() "number"
    }

    %% Relationships
    Student "1" --> "1" Identity : studentId
    Student "n" --> "1" Class : student2class
    Student "n" --> "m" Course : course
    Student "n" <-- "m" Course : students
    %% Class naming
    note for Student "Student Model"
    note for Class "Class Model"
    note for Course "Course Model"
    note for Identity "Identity Model"
```

## Data Model Creation Workflow

### 1. Business Analysis Phase
- Carefully analyze user's business requirement descriptions
- Identify core entities and business objects