Buttons
A modern, customizable button shortcode with gradient styling, icons, and smart link handling.
Basic Usage
The above buttons are created with:
{{< button url="/contact" >}}Contact Us{{< /button >}}
{{< button url="https://example.com" new_tab="true" style="secondary" >}}Visit External Site{{< /button >}}
Style Variants
Primary (Default)
{{< button url="#" style="primary" >}}Primary Button{{< /button >}}
Secondary
{{< button url="#" style="secondary" >}}Secondary Button{{< /button >}}
Outline
{{< button url="#" style="outline" >}}Outline Button{{< /button >}}
Ghost
{{< button url="#" style="ghost" >}}Ghost Button{{< /button >}}
Sizes
Small
Medium (Default)
Large
Extra Large
{{< button url="#" size="sm" >}}Small Button{{< /button >}}
{{< button url="#" size="md" >}}Medium Button{{< /button >}}
{{< button url="#" size="lg" >}}Large Button{{< /button >}}
{{< button url="#" size="xl" >}}Extra Large{{< /button >}}
Alignment
Left (Default)
Center
Right
{{< button url="#" align="left" >}}Left Aligned{{< /button >}}
{{< button url="#" align="center" >}}Center Aligned{{< /button >}}
{{< button url="#" align="right" >}}Right Aligned{{< /button >}}
With Icons
Icon Before Text
Icon After Text
{{< button url="#" icon="arrow-down-tray" >}}Download{{< /button >}}
{{< button url="#" icon="arrow-right" icon_position="right" >}}Continue{{< /button >}}
Rounded Corners
Small Radius
Medium Radius (Default)
Large Radius
Pill Shape
{{< button url="#" rounded="sm" >}}Small Radius{{< /button >}}
{{< button url="#" rounded="md" >}}Medium Radius{{< /button >}}
{{< button url="#" rounded="lg" >}}Large Radius{{< /button >}}
{{< button url="#" rounded="full" >}}Pill Button{{< /button >}}
Advanced Examples
Call-to-Action Button
{{< button url="/signup" style="primary" size="lg" align="center" icon="rocket-launch" >}}Get Started Today{{< /button >}}
External Link with New Tab
{{< button url="https://github.com/hugo-blox/kit" new_tab="true" style="outline" icon="arrow-top-right-on-square" icon_position="right" >}}View on GitHub{{< /button >}}
Download Button
{{< button url="/files/document.pdf" style="secondary" icon="document-arrow-down" rounded="full" >}}Download PDF{{< /button >}}
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
url | string | # | Required. Button destination URL (internal or external) |
text | string | Inner content | Button text (overrides shortcode content) |
new_tab | boolean | false | Whether to open link in new tab |
style | string | primary | Button style: primary, secondary, outline, ghost |
size | string | md | Button size: sm, md, lg, xl |
align | string | left | Button alignment: left, center, right |
icon | string | - | Icon name from Hero Icons |
icon_position | string | left | Icon position: left, right |
rounded | string | md | Border radius: sm, md, lg, xl, full |
disabled | boolean | false | Whether button should be disabled |
Security Features
The button shortcode automatically handles security for external links:
- External links get
rel="noreferrer"attribute - External links opening in new tab get
rel="noopener noreferrer" - Internal links opening in new tab get
rel="noopener"
This ensures safe navigation while maintaining functionality.
Accessibility
The button shortcode includes built-in accessibility features:
- Proper
role="button"attribute aria-labelsupport- Keyboard focus indicators
- High contrast focus rings
- Disabled state handling

José Ángel Martín Baos is an Assistant Professor (PhD) at the Escuela Superior de Informática of the University of Castilla-La Mancha. He obtained his PhD in Advanced Computer Technologies from the University of Castilla-La Mancha in 2023. There, he graduated with honors on both a BSc. in computer science in the year 2018, and a MSc. in computer science in the year 2019.
Since 2016, José Ángel has been working as a researcher in the MAT (Modelos y Algoritmos en Sistemas de Transportes) research group at the University of Castilla-La Mancha. His research focuses on the use of machine learning models and artificial intelligence for solving optimization problems in the field of transportation. Specifically, he has worked on the application of machine learning models for transport demand modeling.