markdown-viewer/skills

Opinionated skills for AI coding agents to create stunning diagrams and visualizations directly in Markdown. These skills extend agent capabilities across...

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Summary Information

Updated 29 minutes ago
Added to GitGenius on September 20th, 2026
Created on January 31st, 2026
Open Issues & Pull Requests: 4 (+0)
GitHub issues: Enabled
Number of forks: 191
Total Stargazers: 3,328 (-1)
Total Subscribers: 10 (+0)

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Open issues: 2
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 92 days
Stale 30+ days: 1
Stale 90+ days: 1

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Closed in 7 days: 0
Comments in 7 days: 0
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Detailed Description

Markdown Viewer Agent Skills is a collection of skills for AI coding agents that enables them to generate diagrams and visualizations directly within Markdown documents.

The tool addresses the need for AI agents to produce rich visual content without leaving the Markdown authoring environment. It provides fourteen skills spanning five rendering engines, each designed to handle specific visualization types. The skills follow the Agent Skills format, making them compatible with multiple AI coding agents including Claude Code, Cursor, and GitHub Copilot. Installation varies by agent: some support automatic detection when skills are placed in a designated directory, while others require manual addition to project knowledge or direct pasting into conversations.

Developers should adopt this tool if they work with AI coding agents and need to generate technical diagrams, data visualizations, or documentation-quality graphics within Markdown. The skill set covers distinct use cases: Vega-Lite and Vega for data-driven charts like bar, line, and scatter plots; infographic templates for KPI cards, timelines, and organizational structures; canvas-based diagrams for mind maps and knowledge graphs; architecture diagrams with multiple layout and style combinations for system design; info cards for editorial-style content; and PlantUML-based skills for domain-specific technical diagrams. The breadth of rendering engines means different visualization needs map to different skills rather than forcing all diagrams through a single engine.

The project shows active maintenance with regular updates to skill definitions and documentation. Development activity includes ongoing refinement of skill templates and layouts, with particular attention to expanding the styling options available across architecture and info card skills. The maintainers continue to add new skills and rendering engine support, indicating sustained investment in broadening the tool's visualization capabilities.