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Best Data Visualization Skills for AI Agents
96 Data Visualization skills for AI coding assistants — ranked by popularity.
This curated collection provides specific skills for AI agents to handle data visualization tasks across various environments. Whether you are building monitoring tools, academic research interfaces, or interactive web applications, these skills extend your AI's capabilities to generate professional-grade visuals. You will find tools for technical tasks like managing Grafana dashboards and scientific plotting with Matplotlib, alongside creative functions for building interactive HTML dashboards and structuring data stories for stakeholders. This library is designed for developers who need their agents to go beyond basic text output and produce structured, actionable visual content. Each skill is packaged as an individual module that plugs directly into your workflow, allowing your AI to handle everything from complex chart generation to infographic layout. By using these targeted skills, your agent can translate raw datasets into clear, readable insights, saving you time on manual front-end development and visual layout design.
Top Data Visualization skills
grafana-dashboards
wshobson
Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.
infographic-creation
antvis
Create beautiful infographics based on the given text content. Use this when users request creating infographics.
streamlit
sverzijl
When working with Streamlit web apps, data dashboards, ML/AI app UIs, interactive Python visualizations, or building data science applications with Python
openalex-database
davila7
Query and analyze scholarly literature using the OpenAlex database. This skill should be used when searching for academic papers, analyzing research trends, finding works by authors or institutions, tracking citations, discovering open access publications, or conducting bibliometric analysis across 240M+ scholarly works. Use for literature searches, research output analysis, citation analysis, and academic database queries.
data-storytelling
wshobson
Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
dashboard-creator
mhattingpete
Create HTML dashboards with KPI metric cards, bar/pie/line charts, progress indicators, and data visualizations. Use when users request dashboards, metrics displays, KPI visualizations, data charts, or monitoring interfaces.
plotly
davila7
Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).
csv-data-summarizer
coffeefuelbump
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
d3-visualization
lyndonkl
Use when creating custom, interactive data visualizations with D3.js—building bar/line/scatter charts from scratch, creating network diagrams or geographic maps, binding changing data to visual elements, adding zoom/pan/brush interactions, animating chart transitions, or when chart libraries (Highcharts, Chart.js) don't support your specific visualization design and you need low-level control over data-driven DOM manipulation, scales, shapes, and layouts.
umap-learn
K-Dense-AI
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
algorithmic-art
anthropics
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
threejs
mrgoonie
Build 3D web apps with Three.js (WebGL/WebGPU). Use for 3D scenes, animations, custom shaders, PBR materials, VR/XR experiences, games, data visualizations, product configurators.
scientific-visualization
davila7
Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.
data-visualization
anthropics
Create effective data visualizations with Python (matplotlib, seaborn, plotly). Use when building charts, choosing the right chart type for a dataset, creating publication-quality figures, or applying design principles like accessibility and color theory.
seaborn
davila7
Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.
kpi-dashboard-design
wshobson
Design effective KPI dashboards with metrics selection, visualization best practices, and real-time monitoring patterns. Use when building business dashboards, selecting metrics, or designing data visualization layouts.
playground
anthropics
Creates interactive HTML playgrounds — self-contained single-file explorers that let users configure something visually through controls, see a live preview, and copy out a prompt. Use when the user asks to make a playground, explorer, or interactive tool for a topic.
infographics
K-Dense-AI
Create professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes.
flight
dvdsgl
Flight canvas for comparing flights and selecting seats. Use when users need to browse flight options and book seats.
baoyu-infographic
JimLiu
Generates professional infographics with 20 layout types and 17 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", or "可视化".
data-analysis
ArtificialAnalysis
High-performance data analysis using Polars - load, transform, aggregate, visualize and export tabular data. Use for CSV/JSON/Parquet processing, statistical analysis, time series, and creating charts.
dashboard-design
mckinsey
USE THIS SKILL FIRST when user wants to create and design a dashboard, ESPECIALLY Vizro dashboards. This skill enforces a 3-step workflow (requirements, layout, visualization) that must be followed before implementation. For implementation and testing, use the dashboard-build skill after completing Steps 1-3.
data-viz-plots
Starlitnightly
Create publication-quality plots and visualizations using matplotlib and seaborn. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).
streaming-mindmap-rendering
SSShooter
Implement real-time streaming mindmap rendering using Mind Elixir in web applications. Supports streaming text parsing and incremental updates.
How to choose a Data Visualization skill
When selecting a skill, consider the target output format and your specific technical environment. Evaluate whether you need low-level control, such as Matplotlib’s scientific plotting, or higher-level abstractions like the dashboard creators. Review the maintenance status of each skill and check if the output requirements match your project stack—for instance, choosing between Streamlit for web-based data apps or standalone HTML files for portable reports. Prioritize skills that provide the specific charts, filtering capabilities, or integration points required by your current visualization project.