How do I choose between terminal and image visualizations?

Terminal formats are best for interactive analysis and quick exploration, while image formats are recommended for final reports and complex architectural diagrams.

Can I create charts manually with text characters?

No, this skill mandates the use of established tools like plotext and sparklines to ensure accuracy and proper scaling; manual character plotting for bars or lines is prohibited.

Does this skill help with data preparation?

Yes, Phase 2 includes a data preparation checklist covering sorting, rounding to appropriate precision, adding calculated columns, and formatting for readability.

What formats are supported for image-based diagrams?

It supports Mermaid for flowcharts, GraphViz for network graphs, Vega-Lite for statistical charts, and DBML for database schemas via the Kroki API.

Creating Data Visualizations

Name: Creating Data Visualizations
Author: tilmon-engineering

bytilmon-engineering

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Data Science & ML

Generates professional terminal-based and image-based data visualizations to enhance analytical insights and documentation.

About

This skill provides a comprehensive framework for transforming raw query results into meaningful visual narratives within Claude Code analysis sessions. It guides users through a structured four-phase process—selection, structuring, creation, and annotation—to produce everything from quick terminal-based sparklines and ASCII charts to high-quality image-based diagrams like Mermaid flows, GraphViz networks, and Vega-Lite charts via Kroki. By enforcing the use of specialized visualization libraries, it ensures data accuracy and presentation quality while providing clear guidance on how to contextualize findings for stakeholders.

Key Features

Standardized 4-phase visualization workflow (Selection to Annotation)
Terminal-based visualizations using plotext, sparklines, and asciichartpy
Integrated annotation guidelines for titles, context, and key takeaways
Image-based diagram generation via Kroki (Mermaid, GraphViz, Vega-Lite)
2 GitHub stars
Automated data structuring with precise rounding and sorting rules

Use Cases

Creating complex data lineage and ER diagrams for database documentation
Generating quick ASCII bar charts for distribution analysis in the terminal
Producing stakeholder-ready reports with embedded Vega-Lite statistical charts

About

Key Features

Standardized 4-phase visualization workflow (Selection to Annotation)
Terminal-based visualizations using plotext, sparklines, and asciichartpy
Integrated annotation guidelines for titles, context, and key takeaways
Image-based diagram generation via Kroki (Mermaid, GraphViz, Vega-Lite)
2 GitHub stars
Automated data structuring with precise rounding and sorting rules

Use Cases

Creating complex data lineage and ER diagrams for database documentation
Generating quick ASCII bar charts for distribution analysis in the terminal
Producing stakeholder-ready reports with embedded Vega-Lite statistical charts