skills/tencentcloudbase/skills/data-model-creation

data-model-creation

Installation
Summary

Advanced data modeling tool for complex multi-table schemas with automated relationship management and ER diagram generation.

  • Designed for enterprise-level scenarios requiring multi-entity relationships, foreign key automation, and visual documentation; most simple table creation should use relational-database-tool directly with SQL
  • Generates Mermaid class diagrams following strict type mapping, naming conventions, and constraint rules for consistent schema design
  • Supports required/unique field constraints, default values, enum types, and display field definitions within the model structure
  • Includes business analysis, Mermaid modeling, and validation phases to ensure completeness and correctness before database implementation
SKILL.md

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
  • Broader feature planning before schema work -> ../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

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.
Weekly Installs
631
GitHub Stars
42
First Seen
Jan 22, 2026
Installed on
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