Summary

md2html transforms AI-generated long-form Markdown documents into polished, self-contained HTML pages, solving the problem of dense, unreadable AI output. It's a portable skill for AI agents, benefiting engineers and researchers by making documentation accessible and engaging without complex build tools.

How It Works

This project leverages AI agents to analyze Markdown content and dynamically assemble it into HTML. Upon invocation, the agent reads the Markdown file alongside repository templates, intelligently selecting presentation components like Mermaid diagrams, step cards, and comparison tables. This approach bypasses traditional build steps, servers, Node, or Python, offering a direct, portable conversion process.

Quick Start & Requirements

Install by cloning the repository to your AI agent's skills directory (e.g., ~/.claude/skills/md2html). Setup is rapid, taking under a minute for users with compatible AI agents and Git. Run conversions using /md2html <your_doc.md>. No specific software prerequisites beyond the AI agent's file I/O capabilities and Git are mentioned.

Highlighted Details

• Enhanced UX: Features a sidebar TOC with scroll-spy, anchor links, code block copy-to-clipboard, and a scroll progress bar.
• Dynamic Component Generation: Automatically converts prose to Mermaid flowcharts, lists to step cards, and comparative text to comparison boxes based on content analysis.
• Self-Contained Output: Generates a single HTML file with embedded CSS/JS; Mermaid CDN is the only external request (inlineable). End-users require zero installation.
• Multi-language UI: Supports 8 languages for UI labels, with automatic translation for others.
• Accessibility: Adheres to WCAG AA contrast, features large touch targets, supports prefers-reduced-motion, and includes a mobile-friendly TOC drawer and print stylesheet.

Maintenance & Community

Maintained by haidang1810 under an MIT license. A roadmap includes planned features like inline Mermaid bundling, additional themes, Gantt/roadmap components, image inlining, and RTL language support. PRs for translations and themes are welcomed. No specific community channels are listed.

Licensing & Compatibility

Released under the permissive MIT license, allowing for commercial use and integration within closed-source projects with minimal restrictions.

Limitations & Caveats

Currently lacks support for Right-to-Left (RTL) languages (e.g., Arabic, Hebrew), rendering them only in LTR format. Planned features like full offline Mermaid support and RTL rendering are still under development.