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Found 8 Skills
Chart selection and data visualization guidance for effective data communication. Use when: creating visualizations, choosing chart types, designing dashboards, or when user mentions data visualization, charts, graphs, or needs help presenting data visually.
Design clear, accessible data visualizations with appropriate chart selection and styling.
Designs effective KPI dashboards with proper metric selection, visual hierarchy, and data visualization best practices. Use when building executive dashboards, creating analytics views, or presenting business metrics.
Chart selection, data viz accessibility, and dashboard patterns. Use when building charts, graphs, or data dashboards.
Builds dashboards, reports, and data-driven interfaces requiring charts, graphs, or visual analytics. Provides systematic framework for selecting appropriate visualizations based on data characteristics and analytical purpose. Includes 24+ visualization types organized by purpose (trends, comparisons, distributions, relationships, flows, hierarchies, geospatial), accessibility patterns (WCAG 2.1 AA compliance), colorblind-safe palettes, and performance optimization strategies. Use when creating visualizations, choosing chart types, displaying data graphically, or designing data interfaces.
Use when you need to choose the right visualization for your data and question, then create a narrated report that highlights insights and recommends actions. Invoke when analyzing data for patterns (trends, comparisons, distributions, relationships, compositions), building dashboards or reports, presenting metrics to stakeholders, monitoring KPIs, exploring datasets for insights, communicating findings from analysis, or when user mentions "visualize this", "what chart should I use", "create a dashboard", "analyze this data", "show trends", "compare these metrics", "report on", "what does this data tell us", or needs to turn data into actionable insights. Apply to business analytics (revenue, growth, churn, funnel, cohort, segmentation), product metrics (usage, adoption, retention, feature performance, A/B tests), marketing analytics (campaign ROI, attribution, funnel, customer acquisition), financial reporting (P&L, budget, forecast, variance), operational metrics (uptime, performance, capacity, SLA), sales analytics (pipeline, forecast, territory, quota attainment), HR metrics (headcount, turnover, engagement, DEI), and any scenario where data needs to become a clear, actionable story with the right visual form.
Data visualization for charts and graphs. Use when user needs "画图/图表/可视化". Creates static PNG or interactive HTML charts from data.
Data visualization design based on Stanford CS448B. Use when: (1) Choosing appropriate chart types for data (2) Selecting visual encodings (position, color, size) (3) Critiquing or improving visualizations (4) Building D3.js visualizations (5) Designing interactions and animations (6) Choosing color palettes for accessibility (7) Visualizing networks or text data Covers Bertin, Mackinlay, Cleveland & McGill principles.