---
name: data-model-creation
description: Optional advanced tool for complex data modeling. For simple table creation, use relational-database-tool directly with SQL statements.
version: 2.17.1
alwaysApply: false
---
## Standalone Install Note
If this environment only installed the current skill, start from the CloudBase main entry and use the published `cloudbase/references/...` paths for sibling skills.
- CloudBase main entry: `https://cnb.cool/tencent/cloud/cloudbase/cloudbase-skills/-/git/raw/main/skills/cloudbase/SKILL.md`
- Current skill raw source: `https://cnb.cool/tencent/cloud/cloudbase/cloudbase-skills/-/git/raw/main/skills/cloudbase/references/data-model-creation/SKILL.md`
Keep local `references/...` paths for files that ship with the current skill directory. When this file points to a sibling skill such as `auth-tool` or `web-development`, use the standalone fallback URL shown next to that reference.
# Data Model Creation
## Activation Contract
### Use this first when
- The user explicitly wants Mermaid `classDiagram` modeling.
- The task needs complex multi-entity relational design, visual ER-style output, or generated data-model structure rather than direct SQL.
- You need to create or update CloudBase data models through the dedicated modeling tools.
### Read before writing code if
- The request mentions data model, ER diagram, Mermaid, relationship graph, or enterprise schema design.
- The user wants to reuse or update an existing published model.
### Then also read
- Direct SQL creation or schema change -> `../relational-database-tool/SKILL.md` (standalone fallback: `https://cnb.cool/tencent/cloud/cloudbase/cloudbase-skills/-/git/raw/main/skills/cloudbase/references/relational-database-tool/SKILL.md`)
- Broader feature planning before schema work -> `../spec-workflow/SKILL.md` (standalone fallback: `https://cnb.cool/tencent/cloud/cloudbase/cloudbase-skills/-/git/raw/main/skills/cloudbase/references/spec-workflow/SKILL.md`)
### Do NOT use for
- Simple `CREATE TABLE`, `ALTER TABLE`, or CRUD tasks.
- Document-database collection design.
- Frontend-only data-shape discussions with no modeling requirement.
### Common mistakes / gotchas
- Using Mermaid modeling for a task that only needs one or two SQL statements.
- Mixing SQL-table design and NoSQL collection design in the same model.
- Generating diagrams without first deciding entity boundaries and ownership relations.
- Publishing a new model before validating the generated fields and relationships.
### Minimal checklist
- Confirm Mermaid modeling is actually needed.
- List the core entities and relationships first.
- Decide whether this is a new model or an update.
- Keep the initial model small unless the user explicitly wants a large enterprise schema.
## Overview
This skill is an **advanced modeling path**, not the default path for database work.
- For most database tasks, use `relational-database-tool` and write SQL directly.
- Use this skill only when diagram-driven modeling adds value.
## Quick routing
### Use `relational-database-tool` instead when
- You need `CREATE TABLE`, `ALTER TABLE`, `INSERT`, `UPDATE`, `DELETE`, or `SELECT`
- The schema is small and already clear
- The user never asked for a visual model
### Use this skill when
- You need multi-entity relationship modeling
- You need Mermaid `classDiagram` output
- You want generated model structure and documentation
- You need a clean modeling pass before SQL implementation
## How to use this skill (for a coding agent)
1. **Clarify the entity set**
- Extract business entities, ownership, and relationship cardinality from the request.
- Prefer 3-5 core entities unless the user clearly asks for more.
2. **Model first, then generate**
- Draft Mermaid `classDiagram` content.
- Validate names, field types, and relationships before calling modeling tools.
3. **Use the right tools**
- Read/list existing models -> `manageDataModel(action="list"|"get"|"docs")`
- Create or update a model -> `modifyDataModel`
4. **Publish carefully**
- Prefer creating with unpublished or draft-like intent first.
- Publish only after checking field names, required constraints, and relationship directions.
## Mermaid generation rules
### Naming
- Class names -> PascalCase
- Field names -> camelCase
- Convert Chinese business descriptions into clear English identifiers
- Keep enum values human-readable when needed
### Type mapping
| Business meaning | Mermaid type |
| --- | --- |
| text | `string` |
| number | `number` |
| boolean | `boolean` |
| enum | `x-enum` |
| email | `email` |
| phone | `phone` |
| URL | `url` |
| image | `x-image` |
| file | `x-file` |
| rich text | `x-rtf` |
| date | `date` |
| datetime | `datetime` |
| region | `x-area-code` |
| location | `x-location` |
| array | `string[]` or another explicit array type |
### Required structure conventions
- Use `required()` only for fields the user explicitly marks as required.
- Use `unique()` only for explicit uniqueness needs.
- Use `display_field()` for the human-facing label field.
- Add concise `<<description>>` notes to important fields.
- Keep relationship labels tied to actual field names rather than vague business prose.
## Minimal example
```mermaid
classDiagram
class User {
username: string <<Username>>
email: email <<Email>>
display_field() "username"
required() ["username", "email"]
unique() ["username", "email"]
}
class Order {
orderNo: string <<Order Number>>
totalAmount: number <<Total Amount>>
userId: string <<User ID>>
display_field() "orderNo"
unique() ["orderNo"]
}
Order "n" --> "1" User : userId
%% Class naming
note for User "用户"
note for Order "订单"
```
## Tool usage guidance
### Read existing models
Use this before updating an existing model or when you need naming consistency:
- `manageDataModel(action="list")`
- `manageDataModel(action="get", name="ModelName")`
- `manageDataModel(action="docs", name="ModelName")`
### Create or update model
Use `modifyDataModel` with:
- complete `mermaidDiagram`
- the correct update mode for create vs update
- a deliberate publish decision
## Best practices
1. Prefer direct SQL unless the user clearly benefits from model-first design.
2. Keep the first model iteration small and reviewable.
3. Separate business entities from implementation-only helper fields.
4. Validate relationship direction and ownership before publishing.
5. After modeling, hand off actual SQL/table work to `relational-database-tool` when needed.