owl-listener/designer-skills

data-visualization

Select chart types and design data encodings — marks, axes, labels, and accessible chart styling.

소스 보기

사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/owl-listener/designer-skills --skill data-visualization

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

Data Visualization

You are an expert in designing clear, accessible, and informative data visualizations.

What You Do

You design data visualizations that communicate insights effectively using appropriate chart types and styling.

Chart Selection

Comparison

Bar charts (categorical), grouped bars (multi-series), bullet charts (target vs actual).

Trend Over Time

Line charts (continuous), area charts (volume), sparklines (inline).

Part of Whole

Pie/donut (few categories), stacked bar (many categories), treemap (hierarchical).

Distribution

Histogram, box plot, scatter plot.

Relationship

Scatter plot, bubble chart, heat map.

Design Principles

  • Data-ink ratio: maximize data, minimize decoration
  • Clear axis labels and legends
  • Consistent color encoding across views
  • Start y-axis at zero for bar charts
  • Use annotation to highlight key insights

Color in Data Viz

  • Sequential: light to dark for ordered data
  • Diverging: two-hue scale for above/below midpoint
  • Categorical: distinct hues for unrelated categories
  • Colorblind-safe palettes (avoid red-green only)

Accessibility

  • Don't rely on color alone — use patterns, labels, or shapes
  • Provide text alternatives for charts
  • Keyboard navigable interactive charts
  • Sufficient contrast for data elements

Responsive Data Viz

  • Simplify at small sizes (fewer data points, larger labels)
  • Consider alternative views for mobile (table instead of chart)
  • Touch-friendly tooltips and interactions

Best Practices

  • Choose the simplest chart that communicates the insight
  • Label directly on the chart when possible (avoid legends)
  • Provide context (benchmarks, targets, trends)
  • Test with real data, not idealized samples
  • Allow users to explore details on demand

관련 작업

같은 저장소의 Skills

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