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data-dashboard

data-dashboard

Create visual data dashboards with charts, KPIs, and insights. TRIGGERS - Use when user wants a dashboard, data visualization, or metrics overview.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: data-dashboard description: | Create visual data dashboards with charts, KPIs, and insights. TRIGGERS - Use when user wants a dashboard, data visualization, or metrics overview.

Data Dashboard Creator

Overview

Creates interactive or static dashboards with KPI cards, charts, and trend analysis. Can output as HTML/React artifacts, Excel, or design specs.

Workflow

Step 1: Define the Dashboard

  1. Purpose: What decisions should this dashboard inform?
  2. Audience: Who views it? (exec, team, clients)
  3. Data source: Where does the data come from?
  4. KPIs: What are the 3-5 most important metrics?
  5. Update frequency: Real-time, daily, weekly, monthly?
  6. Output format: Interactive (HTML/React), Excel, or design spec?

Step 2: Design the Layout

Dashboard hierarchy:

TOP ROW: KPI Cards (3-5 key numbers)
MIDDLE: Primary chart (biggest insight)
BOTTOM LEFT: Secondary chart
BOTTOM RIGHT: Table or list

Step 3: Select Visualizations

Data TypeBest ChartWhen to Use
Trend over timeLine chartRevenue, users, growth
ComparisonBar chartMonth vs month, team vs team
CompositionPie/donutMarket share, budget allocation
DistributionHistogramCustomer segments, pricing
RelationshipScatter plotCorrelation analysis
ProgressGauge/progressGoal tracking
RankingHorizontal barTop performers

Step 4: Build the Dashboard

Create as HTML/React artifact with:

  • Responsive layout
  • Color-coded KPI cards (green = good, red = needs attention)
  • Interactive hover states
  • Clean, professional design
  • Dark or light theme

Output Format

Generate an interactive HTML or React dashboard artifact, or provide design specifications for implementation.

Quality Checklist

  • 3-5 KPI cards at top
  • Most important insight is the largest visual
  • Colors are meaningful (not decorative)
  • Readable on mobile
  • Time period clearly stated
  • Data source noted
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