nbconvert is a mature, actively maintained CLI tool and Python library for converting Jupyter Notebooks (.ipynb) into a wide variety of static formats, including HTML, LaTeX, PDF, Markdown, reStructuredText, AsciiDoc, slides (Reveal.js), executable scripts, and even back to notebook format. The architecture is a pipeline: a notebook is first processed by a chain of configurable preprocessors (e.g., for executing code, removing tags, extracting attachments, converting SVG to PDF), then rendered through Jinja2 templates into the target format, and finally written to disk or stdout via a writer, with optional post-processing (e.g., serving slides). The system is highly extensible via Python entry points for custom exporters, preprocessors, and templates, and all components are configurable through traitlets, enabling both programmatic and command-line use. The codebase is well-structured with clear separation of concerns: exporters (base, template-based, and format-specific), preprocessors (over a dozen), filters (for Jinja2 templates), writers, and postprocessors. The template system supports inheritance and custom syntax for LaTeX. Notable implementation highlights include a custom Markdown parser with LaTeX math support (handling both Mistune v2 and v3), ANSI-to-HTML/LaTeX conversion, SVG-to-PDF conversion with security hardening, and a context manager for directory changes. The test suite is extensive, covering exporters, filters, preprocessors, and the CLI application, with CI testing across multiple Python versions and platforms. While the core functionality is robust, the codebase shows signs of technical drift: some modules are deprecated (e.g., lexers.py), external tool dependencies (pandoc, Inkscape, Playwright) introduce version-specific behavior, and the template system has accumulated complexity with multiple inheritance chains and legacy compatibility paths. The project is actively maintained with recent security fixes and releases, but the breadth of supported formats and external dependencies creates ongoing maintenance overhead.