darkmatter

Parse, render, and compose Markdown documents with frontmatter and transclusion.

3|Updated Jan 10, 2026

Search Tags:#markdown #rendering #composition #terminal #parsing #frontmatter

Ready to run

npx skills add https://github.com/yankeeinlondon/rusty-biscuit --skill darkmatter

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: darkmatter
Source: https://github.com/yankeeinlondon/rusty-biscuit/tree/main/.claude/skills/darkmatter
Command: npx skills add https://github.com/yankeeinlondon/rusty-biscuit --skill darkmatter

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Efficiently parse, render, and compose Markdown documents with frontmatter and transclusions.

Core Features & Use Cases

Markdown parsing (CommonMark + GFM)
Frontmatter handling, merge strategies, and typed extraction
Document composition pipeline (inline pre, transclusion, inline post)
Terminal rendering and HTML output (via biscuit-terminal)
Frontmatter-driven transclusion and toc/linking
Diff and normalization utilities for Markdown

Quick Start

Run the sample to parse a Markdown document and render it to the terminal using the Darkmatter library.

Frequently Asked Questions about darkmatter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I parse and render Markdown in a terminal application?▼

Markdown terminal rendering is handled by integrating a parsing library with biscuit-terminal, enabling direct terminal output. This streamlines content workflows by applying CommonMark and GFM parsing for reliable document display.

What is frontmatter handling in Markdown composition pipelines?▼

Frontmatter handling is the typed extraction and merge strategy of metadata blocks in Markdown documents. It enables frontmatter-driven transclusion and linking, ensuring structured metadata is preserved and utilized during the end-to-end document composition pipeline.

How do I resolve Markdown transclusions during document composition?▼

Markdown transclusion is resolved through a three-phase compose pipeline consisting of inline pre-processing, transclusion resolution, and inline post-processing. This reliably integrates external content and frontmatter-driven links into the final composed document.

Does this Markdown parsing approach support CommonMark and GitHub Flavored Markdown?▼

Yes, Markdown parsing supports both CommonMark and GFM (GitHub Flavored Markdown). This ensures robust document composition and accurate rendering for standard and extended syntax, including tables and frontmatter extraction.

What is the best way to normalize and diff Markdown documents?▼

Markdown normalization and diffing is best handled using dedicated utility functions within a parsing library. These utilities compare document structures and normalize formatting, streamlining content workflows and ensuring consistent HTML or terminal rendering.

Can I extract typed metadata from Markdown frontmatter?▼

Yes, typed extraction from Markdown frontmatter is fully supported. It allows you to parse metadata blocks into structured data formats, enabling frontmatter-driven transclusion and robust document composition workflows without manual data parsing.