book-docusaurus

maneeshanif's avatarfrom maneeshanif

Scaffold, structure, and deploy the Physical AI textbook in Docusaurus with book-aware content and RAG-ready exports. Use when creating or updating the Docusaurus site, adding chapters, configuring sidebar, or deploying to GitHub Pages/Vercel.

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[Knowledge Base]

When & Why to Use This Skill

The book-docusaurus skill automates the end-to-end workflow for creating, structuring, and deploying a Physical AI textbook using the Docusaurus framework. It specializes in generating RAG-ready (Retrieval-Augmented Generation) documentation by enforcing semantic HTML structures and comprehensive frontmatter metadata. This skill streamlines the transition from raw educational content to a professional, searchable, and AI-optimized knowledge platform hosted on GitHub Pages or Vercel.

Use Cases

  • Initial scaffolding of a technical textbook site with pre-configured sidebars, i18n support, and site metadata.
  • Adding new course modules and weekly chapters with standardized MDX templates, including learning outcomes and hardware requirements.
  • Configuring automated CI/CD pipelines via GitHub Actions for seamless deployment and updates to GitHub Pages.
  • Optimizing documentation for AI ingestion by ensuring semantic heading hierarchies and structured frontmatter (tags, modules, weeks) for RAG systems.
  • Implementing custom MDX components like callouts, checklists, and hardware tables to enhance the interactive learning experience.
namebook-docusaurus
descriptionScaffold, structure, and deploy the Physical AI textbook in Docusaurus with book-aware content and RAG-ready exports. Use when creating or updating the Docusaurus site, adding chapters, configuring sidebar, or deploying to GitHub Pages/Vercel.

Book Docusaurus Skill

Instructions

  1. Scaffold the site

    • Ensure Node >=18 is installed
    • Run npx create-docusaurus@latest physical-ai-book classic in project root or /docs
    • Configure docusaurus.config.js with site metadata, GitHub Pages URLs, i18n (en default)

  2. Structure content

    • Build sidebars.js for Quarter overview, Modules 1-4, Capstone, Assessments, Hardware kits, Cloud option
    • Create MDX stubs per module/week with learning outcomes and tasks
    • Add capstone outline

  3. Authoring affordances

    • Add MDX components for callouts, checklists, hardware tables, code blocks
    • Enable search (Algolia DocSearch placeholder) and local search plugin for dev

  4. Deploy

    • Add GitHub Actions workflow for GH Pages (npm ci, npm run build, npm run deploy)
    • Document Vercel deploy steps (import repo, build command npm run build, output build)

  5. RAG-readiness

    • Enforce frontmatter fields: title, description, module, week, tags
    • Keep headings semantic (h2 for weeks, h3 for sections)
    • Avoid heavy client-side rendering for core text
    • Export ingestion guidance: markdown path glob, ignore build/static

Examples

# Create new chapter
mkdir -p docs/module-1/week-1
cat > docs/module-1/week-1/intro.mdx << 'EOF'
---
title: Introduction to Physical AI
description: Overview of embodied intelligence and humanoid robotics
module: 1
week: 1
tags: [physical-ai, robotics, introduction]
---

# Introduction to Physical AI

Content here...
EOF

# Build and test locally
npm run build
npm run serve

Definition of Done

  • npm run build passes; site renders outline and sample content
  • Sidebar matches course hierarchy; links valid
  • GH Pages workflow present; deploy instructions written
  • Content annotated with frontmatter and semantic headings suitable for chunking