Data Model Creation

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 a new model -> modifyDataModel (compatibility name; create-only)

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

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

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 creating related models, checking naming consistency, or assessing how an existing model is defined:

• manageDataModel(action="list")
• manageDataModel(action="get", name="ModelName")
• manageDataModel(action="docs", name="ModelName")

Create model

Use modifyDataModel with:

• a complete mermaidDiagram
• action="create" when you want to create new models
• a deliberate publish decision
• clear awareness that updating existing model structures is not currently supported by this tool

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.