create-viz Skill
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. Published by anthropics in knowledge-work-plugins.
Decision snapshot
Is this a fit?
Data analysis, Design and media, Writing, Includes SKILL.md
Compatibility not yet detected.
Permission behavior not yet detected.
Copy skill directory
2 months ago · Apache-2.0 license
No specific cautions were detected. Review the source and requested permissions before installing.
What is create-viz Skill?
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. Published by anthropics in knowledge-work-plugins. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Data analysis
- Design and media
- Writing
- Data analysis use cases
- Design and media use cases
Declared skill metadata
- Source file: data/skills/create-viz/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use create-viz Skill
- Use it for data analysis.
- Use it for design and media.
- Use it for writing.
Built with
Editorial notes
Source
- Creator: anthropics
- Repository: anthropics/knowledge-work-plugins
- Skill file: data/skills/create-viz/SKILL.md
What it does
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.
Skill instructions
/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 /create-viz <data source [chart type] [additional instructions] 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
Verified compatibility and discovery
Frequently asked questions
What is create-viz?
create-viz is a open-source AI agent skill with Copy skill directory. 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.
Who is create-viz best for?
create-viz is best for reusing agent instructions, scripts, and references, data analysis workflows, design and media workflows, writing workflows.
How do I install create-viz?
Install or run create-viz using Copy skill directory. Check create-viz for the latest setup command.
Is create-viz actively maintained?
create-viz may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
