book-metrics-generator

The book-metrics-generator is a diagnostic tool designed for authors and educators building intelligent textbooks using the MkDocs Material framework. It serves as a comprehensive auditing utility that tracks the development lifecycle of course content by quantifying educational, technical, and structural components. By executing an automated scan of your project directory, this skill provides actionable insights into content density, completeness, and pedagogical distribution, which is essential for project status reporting and quality assurance before publication.

• Automatically generates book-metrics.md with overall project statistics and chapter-metrics.md for granular, per-chapter performance breakdowns.

• Analyzes specific educational components including learning concepts from CSV graphs, glossary term density, FAQ coverage, and chapter-level quiz question counts.

• Technical evaluation of visual and interactive assets such as diagrams, LaTeX-based equations, and p5.js MicroSims to ensure learning engagement benchmarks are met.

• Calculates physical page-equivalent estimates based on word counts and component density (diagrams and simulations), helping teams track project scope and scale.

• Standardizes reporting across multiple textbook projects by following consistent file detection patterns in docs/chapters, docs/sims, and root directory markdown files.

• Ideal for educational content developers, technical writers, and instructional designers working on complex, multi-chapter digital textbooks.

• Practical for use cases such as assessing content completeness after major revision cycles, comparing metrics over time to identify growth trends, and preparing documentation for stakeholders.

• Requirements include a standard intelligent textbook structure with defined chapters and supporting files like learning-graph.csv, glossary.md, and quiz.md files.

• Users should note the specific regex-based detection patterns: it counts H2/H3 headers for glossary/FAQs, looks for H4 'Diagram:' headers, and excludes code blocks to ensure word counts represent prose rather than logic.

• The output includes integrated tables that can be directly mapped to your mkdocs.yml navigation, keeping your project metrics always visible and accessible to students and collaborators.