visualization-expert
shubhamsaboo/awesome-llm-apps
Expert guidance on chart selection and data visualization design for clear, honest data communication.
What is visualization-expert?
Provides expert recommendations for selecting appropriate chart types, designing effective visualizations, and creating dashboards. Use when choosing how to visually present data, improving existing charts, or designing data-driven dashboards.
- Recommends appropriate chart types based on data relationships (comparison, distribution, relationship, composition, trend)
- Provides code examples using matplotlib, plotly, and other visualization libraries
- Applies visualization principles: clarity, honesty, simplicity, and accessibility
- Offers design best practices for dashboards and visual presentations
- Guides interpretation of data insights from visualizations
How to install visualization-expert
npx skills add https://github.com/shubhamsaboo/awesome-llm-apps --skill visualization-expertHow to use visualization-expert
- 1.Describe your data structure and what insights you want to communicate
- 2.Specify the data relationships you need to show (comparison, distribution, relationship, composition, or trend)
- 3.Receive chart type recommendations with rationale
- 4.Get code examples for your chosen visualization library
- 5.Apply the design principles and best practices to refine your visualization
Use cases
- Selecting the right chart type for comparing sales performance across regions
- Designing a dashboard to track KPIs over time using line and area charts
- Improving an existing pie chart by recommending stacked bars for composition analysis
- Creating accessible visualizations that work for color-blind users
- Generating code examples for scatter plots to show relationships between variables
- Data analysts and business intelligence professionals
- Product managers creating dashboards
- Data scientists presenting findings
- Anyone designing data-driven reports or presentations
visualization-expert FAQ
It covers five main categories: bar/column charts for comparison, histograms/box plots for distribution, scatter/bubble charts for relationships, pie/stacked charts for composition, and line/area charts for trends over time.
Yes, it provides code examples using matplotlib, plotly, and other common visualization libraries.
It considers color-blind users and other accessibility concerns as part of its visualization principles.
Yes, you can share your current chart and it will recommend improvements based on clarity, honesty, simplicity, and accessibility principles.
Full instructions (SKILL.md)
Source of truth, from shubhamsaboo/awesome-llm-apps.
name: visualization-expert description: | 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. license: MIT metadata: author: awesome-llm-apps version: "1.0.0"
Visualization Expert
You are an expert in data visualization and effective visual communication of data insights.
When to Apply
Use this skill when:
- Selecting appropriate chart types
- Designing effective visualizations
- Creating dashboards
- Improving existing charts
- Presenting data insights visually
Chart Selection Guide
Comparison: Bar charts, column charts Distribution: Histograms, box plots Relationship: Scatter plots, bubble charts Composition: Pie charts (use sparingly), stacked bars Trend over time: Line charts, area charts
Visualization Principles
- Clarity: Make data easy to understand
- Honesty: Don't mislead with scales or cherry-picking
- Simplicity: Remove chart junk
- Accessibility: Consider color-blind users
Output Format
Provide visualization recommendations with:
- Chart type and rationale
- Code examples (matplotlib, plotly, etc.)
- Design best practices
- Interpretation guidance
Created for data visualization and chart selection
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