Agent skill

Data Model Creation

by TencentCloudBase in TencentCloudBase/CloudBase-AI-Toolkit

[Deprecated] Optional advanced tool for complex data modeling.

MITAuto-check passedDatabases

Install Data Model Creation

skills CLI

$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill data-model-creation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install TencentCloudBase/CloudBase-AI-Toolkit data-model-creation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/TencentCloudBase/CloudBase-AI-Toolkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/config/source/skills/data-model-creation .claude/skills/data-model-creation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "data-model-creation" agent skill from https://github.com/TencentCloudBase/CloudBase-AI-Toolkit/tree/main/config/source/skills/data-model-creation into .claude/skills/data-model-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-model-creation", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/TencentCloudBase/CloudBase-AI-Toolkit/tree/main/config/source/skills/data-model-creation

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill data-model-creation -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install TencentCloudBase/CloudBase-AI-Toolkit data-model-creation --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TencentCloudBase/CloudBase-AI-Toolkit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/config/source/skills/data-model-creation .agents/skills/data-model-creation && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "data-model-creation" agent skill from https://github.com/TencentCloudBase/CloudBase-AI-Toolkit/tree/main/config/source/skills/data-model-creation into .agents/skills/data-model-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-model-creation", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill data-model-creation -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install TencentCloudBase/CloudBase-AI-Toolkit data-model-creation --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TencentCloudBase/CloudBase-AI-Toolkit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/config/source/skills/data-model-creation .cursor/skills/data-model-creation && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "data-model-creation" agent skill from https://github.com/TencentCloudBase/CloudBase-AI-Toolkit/tree/main/config/source/skills/data-model-creation into .cursor/skills/data-model-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-model-creation", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/TencentCloudBase/CloudBase-AI-Toolkit.git --path config/source/skills/data-model-creation

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill data-model-creation -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install TencentCloudBase/CloudBase-AI-Toolkit data-model-creation --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TencentCloudBase/CloudBase-AI-Toolkit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/config/source/skills/data-model-creation .gemini/skills/data-model-creation && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "data-model-creation" agent skill from https://github.com/TencentCloudBase/CloudBase-AI-Toolkit/tree/main/config/source/skills/data-model-creation into .gemini/skills/data-model-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-model-creation", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install TencentCloudBase/CloudBase-AI-Toolkit data-model-creation

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill data-model-creation -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/TencentCloudBase/CloudBase-AI-Toolkit.git skills-src && mkdir -p .github/skills && cp -r skills-src/config/source/skills/data-model-creation .github/skills/data-model-creation && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "data-model-creation" agent skill from https://github.com/TencentCloudBase/CloudBase-AI-Toolkit/tree/main/config/source/skills/data-model-creation into .github/skills/data-model-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-model-creation", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill data-model-creation -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install TencentCloudBase/CloudBase-AI-Toolkit data-model-creation --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TencentCloudBase/CloudBase-AI-Toolkit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/config/source/skills/data-model-creation .opencode/skills/data-model-creation && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "data-model-creation" agent skill from https://github.com/TencentCloudBase/CloudBase-AI-Toolkit/tree/main/config/source/skills/data-model-creation into .opencode/skills/data-model-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-model-creation", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: data-model-creation
GitHub stars: 1.1k
Used in: 1 other repo
Token cost: ~1.8k tokens
SKILL.md length: 738 words
Files: 1
Skills in repo: 49
Repo updated: Oct 6, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

[Deprecated] Optional advanced tool for complex data modeling.

Works in 4 steps: Clarify the entity set → Model first, then generate → Use the right tools → …
Tasks that involve Database schema design
SKILL.md covers Sibling skills (local only), Activation Contract, Overview and Quick routing, plus 5 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Data Model Creation is an agent skill from TencentCloudBase/CloudBase-AI-Toolkit. [Deprecated] Optional advanced tool for complex data modeling. For simple MySQL table creation, use relational-database-tool directly; for PostgreSQL / CloudBase PG schema work, use postgresql-development. New environments should use PostgreSQL DDL via queryPgDatabase/managePgDatabase — see postgresql-development skill instead.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Databases, covering Database schema design and Diagrams. It works with PostgreSQL, MySQL, Mermaid and SQL. The repository describes itself as: Backend for AI coding agents on CloudBase — database, auth, functions via Plugin, Skills & MCP. The licence is MIT.

When your agent uses it

Tasks that involve Database schema design
Tasks that involve Diagrams

Example prompts

“/data-model-creation”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

Clarify the entity set
Model first, then generate
Use the right tools
Publish carefully

What it can do on your machine

Read from SKILL.md and the folder at commit ea2c202. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are mermaid).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Data Model Creation loads about 1.8k tokens when it runs. Until then it costs about 87 tokens; SKILL.md has 738 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~87
When it runs · the whole SKILL.md, loaded when a task matches: ~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from TencentCloudBase/CloudBase-AI-Toolkit at commit ea2c202, republished under its MIT licence (© TencentCloudBase). 738 words, ~1,751 tokens.

Download SKILL.mdSave it as .claude/skills/data-model-creation/SKILL.md (or your agent's skills folder).

name: data-model-creation
description: [Deprecated] Optional advanced tool for complex data modeling. For simple MySQL table creation, use relational-database-tool directly; for PostgreSQL / CloudBase PG schema work, use postgresql-development. New environments should use PostgreSQL DDL via queryPgDatabase/managePgDatabase — see postgresql-development skill instead.
version: 2.34.8
alwaysApply: false
metadata.priority: 5
metadata.deprecated: true

Sibling skills (local only)

Sibling CloudBase skills ship beside this skill. Use local relative paths such as ../auth-tool-cloudbase/SKILL.md.

If a referenced sibling skill file is missing from this environment, ask the user to install the full CloudBase plugin (or the missing skill). Do not HTTP-fetch remote skill or protocol markdown into the agent context.

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 CloudBase data models through the dedicated modeling tools, or you need to inspect an existing model before planning follow-up changes.

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 MySQL SQL creation or schema change -> ../relational-database-mcp-cloudbase/SKILL.md
PostgreSQL / CloudBase PG schema work -> ../postgresql-development-cloudbase/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 MySQL database tasks, use relational-database-mcp-cloudbase and write SQL directly. If the task says PostgreSQL, CloudBase PG, PG mode, app.rdb(), queryPgDatabase, managePgDatabase, or RLS, use postgresql-development-cloudbase instead.
Use this skill only when diagram-driven modeling adds value.

Quick routing

Use `relational-database-mcp-cloudbase` instead when

You need MySQL CREATE TABLE, ALTER TABLE, INSERT, UPDATE, DELETE, or SELECT
The schema is small and already clear
The user never asked for a visual model
The task does not mention PostgreSQL / CloudBase PG / PG mode / app.rdb() / queryPgDatabase / managePgDatabase / RLS

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

Show full SKILL.md (333 more words)Show less

How to use this skill (for a coding agent)

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.
Model first, then generate
- Draft Mermaid classDiagram content.
- Validate names, field types, and relationships before calling modeling tools.
Use the right tools
- Read/list existing models -> manageDataModel(action="list"|"get"|"docs")
- Create a new model -> modifyDataModel (compatibility name; create-only)
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 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

Prefer direct SQL unless the user clearly benefits from model-first design.
Keep the first model iteration small and reviewable.
Separate business entities from implementation-only helper fields.
Validate relationship direction and ownership before publishing.
After modeling, hand off actual MySQL SQL/table work to relational-database-mcp-cloudbase when needed. For PostgreSQL / CloudBase PG tables, hand off to postgresql-development-cloudbase instead.

Files

Just SKILL.md in config/source/skills/data-model-creation of TencentCloudBase/CloudBase-AI-Toolkit.

Open the folder on GitHubat commit ea2c202

Used in 1 other repository

We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in TencentCloudBase/CloudBase-AI-Toolkit, which our catalogue first saw on October 7, 2026.

infometa/workbuddyskillsconnectors/cloudbase/skills/references/data-model-creation

Compare with similar skills

Data Model Creation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Data Model Creation compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Data Model Creation this skillTencentCloudBase/CloudBase-AI-Toolkit	1.1k	1 repos	~1.8k	Automated safety check: Pass	MIT	yesterday
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Golang Databaseunxed/f4	240	2 repos	~2.9k	Automated safety check: Pass	MIT	today
DB Migrationhiromaily/go-crypto-wallet	128	—	~652	Automated safety check: Pass	MIT	5 mo ago
Expert DatabaseReJeCtAll/ExpertTeam-Codex	113	—	~692	Automated safety check: Pass	MIT	3 mo ago
SQL ProJeffallan/claude-skills	12k	—	~1.3k	Automated safety check: Pass	MIT	4 days ago

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Works with

Questions about Data Model Creation

What does Data Model Creation do?

[Deprecated] Optional advanced tool for complex data modeling. Data Model Creation is an agent skill from TencentCloudBase/CloudBase-AI-Toolkit. [Deprecated] Optional advanced tool for complex data modeling.

When should I use Data Model Creation?

Data Model Creation fits situations like: tasks that involve Database schema design; tasks that involve Diagrams.

How do I install Data Model Creation in Claude Code?

Run `npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill data-model-creation -a claude-code`. Or copy the skill folder (config/source/skills/data-model-creation in TencentCloudBase/CloudBase-AI-Toolkit) into .claude/skills/data-model-creation in your project. Claude Code loads it when a task matches its description.

How do I install Data Model Creation in Codex?

Run `npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill data-model-creation -a codex`. Or copy the skill folder (config/source/skills/data-model-creation in TencentCloudBase/CloudBase-AI-Toolkit) into .agents/skills/data-model-creation in your project. Codex loads it when a task matches its description.

Can I use Data Model Creation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill data-model-creation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/data-model-creation, .gemini/skills/data-model-creation, .github/skills/data-model-creation and .opencode/skills/data-model-creation in your project.

What does Data Model Creation need to run?

SKILL.md names no scripts, command-line tools or credentials: Data Model Creation is instructions for the agent only.

Does Data Model Creation access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Data Model Creation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Data Model Creation use?

Data Model Creation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Data Model Creation use?

About 1.8k tokens (SKILL.md is roughly 7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Data Model Creation?

Skills that share tags, products or a category with Data Model Creation: Sql2er (ystemsrx/sql_to_ER, 188 stars), Golang Database (unxed/f4, 240 stars), DB Migration (hiromaily/go-crypto-wallet, 128 stars) and Expert Database (ReJeCtAll/ExpertTeam-Codex, 113 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Data Model Creation?

TencentCloudBase (a GitHub organization) maintains it in TencentCloudBase/CloudBase-AI-Toolkit, which has 1,132 GitHub stars. The repository holds 49 skills in this directory. The repository was last updated on October 6, 2026.

Source: TencentCloudBase/CloudBase-AI-Toolkit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Data Model Creation

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Sibling skills (local only)

Data Model Creation

Activation Contract

Use this first when

Read before writing code if

Then also read

Do NOT use for

Common mistakes / gotchas

Minimal checklist

Overview

Quick routing

Use relational-database-mcp-cloudbase instead when

Use this skill when

How to use this skill (for a coding agent)

Mermaid generation rules

Naming

Type mapping

Required structure conventions

Minimal example

Tool usage guidance

Read existing models

Create model

Best practices

Files

Used in 1 other repository

Compare with similar skills

Similar skills

More from TencentCloudBase/CloudBase-AI-Toolkit

Related

Questions about Data Model Creation

Use `relational-database-mcp-cloudbase` instead when