name: ant-design description: Ant Design React component library — enterprise UI, forms, tables, charts, theming, ProComponents domain: content tags:
- ant
- content-creation
- design
- digital-content
- media
Overview
Ant Design is an enterprise-grade React UI library with 60+ components, a design system, and ProComponents for advanced business scenarios. Widely used for admin dashboards, CMS, and data-heavy applications.
Capabilities
- 60+ polished components with consistent design language
- ConfigProvider for global theming (colors, locale, prefixCls)
- Form component with validation, dependencies, dynamic fields
- Table with sorting, filtering, pagination, virtual scroll
- ProComponents: ProTable, ProForm, ProLayout, ProDescriptions
- Day.js integration for date components
- Ant Design Icons (300+)
When to Use
- Building enterprise admin dashboards and CMS
- Need advanced form handling with complex validation
- Want a complete design system with minimal customization
- Building data-heavy applications with tables, charts, filters
When NOT to Use
- Task is about content strategy, not creation (use strategy skills)
- Task is about content distribution (use distribution skills)
- You need to analyze content performance (use analytics skills)
- Task is about content moderation (use moderation tools)
- You don't have content guidelines
- Task requires domain expertise (consult experts)
Pseudo Code
The ant-design workflow follows a standard pipeline pattern.
Core flow:
# ant-design primary flow
input = prepare(raw_data)
result = process(input, config={ant, charts, component, design, enterprise})
validate(result)
deliver(result)
Error handling:
on error:
log(error_details)
retry_with_backoff(max=3)
if still_failing: alert_and_escalate()
Core Workflow
# ant-design primary flow
input = prepare(raw_data)
result = process(input, config={ant, charts, component, design, enterprise})
validate(result)
deliver(result)
Error Handling
on error:
log(error_details)
retry_with_backoff(max=3)
if still_failing: alert_and_escalate()
Installation
npm install antd @ant-design/icons
# ProComponents for advanced patterns
npm install @ant-design/pro-components
Theme Configuration
import { ConfigProvider } from "antd"
function App() {
return (
<ConfigProvider
theme={{
token: {
colorPrimary: "#1677ff",
borderRadius: 6,
fontFamily: "Inter, sans-serif",
},
}}
>
<YourApp />
</ConfigProvider>
)
}
Form with Validation
import { Form, Input, Select, Button, message } from "antd"
export function UserForm() {
const [form] = Form.useForm()
const onFinish = (values) => {
message.success("Saved!")
console.log(values)
}
return (
<Form form={form} layout="vertical" onFinish={onFinish}>
<Form.Item name="name" label="Name" rules={[{ required: true }]}>
<Input />
</Form.Item>
<Form.Item name="role" label="Role" rules={[{ required: true }]}>
<Select options={[{ value: "admin" }, { value: "user" }]} />
</Form.Item>
<Button type="primary" htmlType="submit">Save</Button>
</Form>
)
}
ProTable
import { ProTable } from "@ant-design/pro-components"
const columns = [
{ title: "Name", dataIndex: "name", sorter: true },
{ title: "Status", dataIndex: "status", valueEnum: { active: "Active", inactive: "Inactive" } },
{ title: "Created", dataIndex: "createdAt", valueType: "date" },
]
export function UserTable() {
return (
<ProTable
columns={columns}
request={async (params) => {
const data = await fetchUsers(params)
return { data: data.list, total: data.total }
}}
search={{ labelWidth: "auto" }}
pagination={{ pageSize: 20 }}
/>
)
}
Common Patterns
- ConfigProvider locale:
<ConfigProvider locale={zhCN}>for i18n - Form dependencies:
shouldUpdate={(prev, cur) => prev.field !== cur.field}for conditional fields - Table virtual scroll:
virtualprop for 1000+ row performance - message/notification:
message.success(),notification.error()for feedback - Responsive Grid:
<Row gutter={[16, 16]}><Col xs={24} md={12}>...</Col></Row>
How to Use
- Define content goal (traffic, engagement, conversion, brand awareness)
- Research target audience pain points and search intent
- Generate content using appropriate AI tools
- Edit and humanize output for authenticity
- Optimize for target platform (SEO, hashtags, format)
- Schedule and distribute across channels
- Measure performance and iterate
Red Flags
- AI-generated content sounds robotic: Always run through humanizer before publishing
- Engagement dropping week-over-week: Content fatigue or algorithm change — vary formats
- Duplicate content across platforms: Adapt content per platform, don't just cross-post
- No content calendar: Sporadic posting kills audience retention
- Ignoring analytics: Content without measurement is just publishing, not marketing
Verification
- Skill output matches expected behavior
Process
- Analyze the task requirements
- Apply domain expertise
- Verify output quality