What is a PortletConfig in this skill?

A PortletConfig is a configuration object that defines a specific widget's identifier, display title, grid position (x, y, w, h), and analysis settings within a dashboard.

How do dashboard filters work?

Filters are defined at the dashboard level and can be selectively mapped to specific portlets using the dashboardFilterMapping array to ensure data consistency across the view.

Can I use different layout modes?

Yes, the skill supports both 'grid' layout (a standard 12-column system) and 'rows' layout strategies to suit different design requirements.

What is the recommended way to configure charts?

It is recommended to use the analysisConfig field, which provides a unified structure for versioning, analysis types, active views, and specific chart display settings.

Does it support performance optimization for many charts?

Yes, the system defaults to lazy loading portlets as they scroll into view, though you can use the eagerLoad property to prioritize specific critical widgets.

Drizzle Cube Dashboard Configurator

Name: Drizzle Cube Dashboard Configurator
Author: cliftonc

bycliftonc

분석 및 모니터링

Generates and configures interactive analytics dashboards with flexible grid layouts and data-driven portlets for Drizzle Cube applications.

소개

The dc-dashboard-config skill streamlines the creation of sophisticated business intelligence dashboards by providing structured guidance on DashboardConfig and PortletConfig implementations. It enables developers to quickly define complex layouts, map universal filters, and configure a wide array of visualization types including KPI deltas, funnel charts, and time-series graphs. By leveraging the latest analysisConfig patterns, this skill ensures consistent data presentation, optimized performance through lazy loading, and seamless integration with Drizzle Cube enabled applications.

주요 기능

0 GitHub stars
Flexible 12-column grid and row-based layout management
Integrated color palette and display theme management
Performance-optimized lazy loading and eager loading configurations
Support for diverse visualizations including KPI, bar, line, funnel, and table charts
Dashboard-level filter mapping for universal data scoping

사용 사례

Building executive-level KPI dashboards with real-time performance metrics
Creating detailed sales funnel visualizations and revenue trend reports
Designing interactive data tables with custom filtering and sorting for end-users

소개

주요 기능

0 GitHub stars
Flexible 12-column grid and row-based layout management
Integrated color palette and display theme management
Performance-optimized lazy loading and eager loading configurations
Support for diverse visualizations including KPI, bar, line, funnel, and table charts
Dashboard-level filter mapping for universal data scoping

사용 사례

Building executive-level KPI dashboards with real-time performance metrics
Creating detailed sales funnel visualizations and revenue trend reports
Designing interactive data tables with custom filtering and sorting for end-users