Agent skill · design visual · anthropics
create-viz
Create publication-quality visualizations with Python. Use when turning query results or a DataFrame into a chart, selecting the right chart type for a trend or comparison, generating a plot for a report or presentation, or needing an interactive chart with hover and zoom.
Why this skill is useful
Provides specific Python code templates for generating various types of visualizations that the AI wouldn't reliably generate on its own.
What it needs
Requires matplotlib, pandas, plotly, python, seaborn installed locally. About 3k tokens when loaded. Last updated 2026-08-07. 23,345 stars on the source repository.
What this skill does
/create-viz - Create Visualizations If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md. Create publication-quality data visualizations using Python. Generates charts from data with best practices for clarity, accuracy, and design. Usage Workflow 1. Understand the Request Determine: Data source: Query results, pasted data, CSV/Excel file, or data to be queried Chart type: Explicitly requested or needs to be recommended Purpose: Exploration, presentation, report, dashboard component Audience: Technical team, executives, external stakeholders 2. Get the Data If data warehouse is connected and data needs querying: 1. Write and execute the query 2. Load results into a pandas DataFrame If data is pasted or uploaded: 1. Parse the data into a pandas DataFrame 2. Clean and prepare as needed (type conversions, null handling) If data is from a previous analysis in the conversation: 1. Reference the existing data 3. Select Chart Type If the user didn't specify a chart type, recommend one based on the data and question: Data Relationship Recommended Chart --- --- Trend over time Line chart Comparison across categories Bar chart (horizontal if many categories) Part-to-whole composition Stacked bar or area chart (avoid pie charts unless <6 categories) Distribution of values Histogram or box plot Correlation between two variables Scatter plot Two-variable comparison over time Dual-axis line or grouped bar Geographic data Choropleth map Ranking Horizontal bar chart Flow or process Sankey diagram Matrix of relationships Heatmap Explain the recommendation briefly if the user didn't specify. 4. Generate the Visualization Write Python code using one of these libraries based on the need: matplotlib + seaborn: Best for static, publication-quality charts. Default choice. plotly: Best for interactive charts or when the user requests interactivity. Code requirements: 5. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills anthropics/create-viz