markdown-plus-author

Write and rewrite structured Markdown+ documents with block IDs and inline metadata.

Updated Aug 22, 2026
One-click install
npx skills add https://github.com/JustinChangTW/ai-skills-core --skill markdown-plus-author-justinchangtw
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: markdown-plus-author
Source: https://github.com/JustinChangTW/ai-skills-core/tree/main/skills/06-writing-editing/markdown-plus-author
Command: npx skills add https://github.com/JustinChangTW/ai-skills-core --skill markdown-plus-author-justinchangtw

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve? Plain Markdown is easy for humans but hard for AI agents to query, and HTML is readable but token-expensive and noisy. This Skill produces Markdown+ documents: plain CommonMark that stays valid in any viewer while adding addressable bullet-list blocks with **#id** headers and inline-code key:value metadata, so one source serves both AI parsers and human readers. ## Core Features & Use Cases - Fresh authoring: Write dev notes, decision records (ADRs), tech specs, status reports, runbooks, research reports, and executive briefs as block-structured Markdown+ with a controlled metadata vocabulary. - Markdown and HTML rewriting: Convert existing plain Markdown or HTML into Markdown+, stripping scripts, styles, base64 media, and layout wrappers while preserving code fences and ASCII trees byte-for-byte. - Validation contract: Enforces a 14-point output contract covering unique kebab-case IDs, closed type: vocabulary, prose companions for every figure/table/KPI, external media paths, and caption conventions. - Use Case: Convert an HTML executive dashboard with KPI cards into a Markdown+ document where each KPI becomes a type:kpi block with value:, target:, and delta: metadata plus a prose summary, cutting output tokens versus Heavy HTML by roughly 60%. ## Quick Start Ask the AI to rewrite your existing Markdown or HTML document into Markdown+ format with block IDs, type metadata, and prose companions for every table and figure.

Frequently Asked Questions about markdown-plus-author

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

FAQPage Schema
How do I convert Markdown or HTML into Markdown+ format?▼

Provide the source document and ask for a Markdown+ rewrite. The Skill classifies the input, plans a block manifest, assigns types from a controlled vocabulary, and outputs a single CommonMark-valid file with block IDs, metadata, captions, and prose companions.

What is Markdown+ and how is it different from plain Markdown?▼

Markdown+ is plain Markdown plus three habits: substantive sections become bullet-list blocks with `**#id**` headers and inline-code metadata, binary media uses external relative paths, and every figure or table gets a prose companion. It stays valid CommonMark, unlike `:::` directive dialects.

Does Markdown+ work in GitHub, Obsidian, and VS Code preview?▼

Yes. Markdown+ source is valid CommonMark, so standard viewers render it as nested bullet lists, inline code, italic captions, and standard tables with no unrendered directives. A dedicated viewer can additionally project it into rich HTML with nav, pills, and cards.

When should I not use Markdown+ for a document?▼

Avoid it for slide decks, one-off emails or chat replies, long-form prose essays where block structure harms the writing, and short documents with fewer than two substantive sections. Plain Markdown or a dedicated format fits those cases better.

Why must code fences and ASCII trees be preserved verbatim?▼

LLM rewrites commonly flatten directory trees into paragraphs, drop fence markers, or re-align whitespace, permanently destroying structure. The Skill treats fenced code, box-drawing trees, and aligned art as byte-for-byte protected content inside fenced blocks.

How does Markdown+ handle images, charts, and large tables?▼

All binary media and SVG are referenced by relative path, never base64 or inline. Tables over roughly 30 rows move to an external CSV via `data-source:`, and large chart specs are extracted to external JSON files.