The communication of technical insight in scientific manuscripts often relies on ad-hoc formatting choices, resulting in inconsistent visual emphasis and limited portability across document classes. This paper introduces ktbox, a modular LaTeX framework that unifies semantic color palettes, structured highlight boxes, taxonomy trees, and author metadata utilities into a coherent system for scholarly writing. The framework is distributed as a set of lightweight, namespaced components: ktcolor.sty for semantic palettes, ktbox.sty for structured highlight and takeaway environments, ktlrtree.sty for taxonomy trees with fusion and auxiliary annotations, and ktorcid.sty for ORCID-linked author metadata. Each component is independently usable yet interoperable, ensuring compatibility with major templates such as IEEEtran, acmart, iclr conference, and beamer. Key features include auto-numbered takeaway boxes, wide-format highlights, flexible taxonomy tree visualizations, and multi-column layouts supporting embedded tables, enumerations, and code blocks. By adopting a clear separation of concerns and enforcing a consistent naming convention under the kt namespace, the framework transforms visual styling from cosmetic add-ons into reproducible, extensible building blocks of scientific communication, improving clarity, portability, and authoring efficiency across articles, posters, and presentations.

翻译：科学手稿中技术见解的传达常依赖于临时性的格式选择，导致视觉强调不一致且跨文档类别的可移植性有限。本文介绍KTBox，一个模块化的LaTeX框架，它将语义调色板、结构化高亮框、分类树和作者元数据工具统一整合为学术写作的连贯系统。该框架以一组轻量级、带命名空间的组件形式发布：ktcolor.sty用于语义调色板，ktbox.sty用于结构化高亮与要点摘录环境，ktlrtree.sty用于支持融合与辅助标注的分类树，ktorcid.sty用于关联ORCID的作者元数据。每个组件既可独立使用又能相互协作，确保与IEEEtran、acmart、iclr会议模板及beamer等主流模板的兼容性。核心功能包括自动编号的要点框、宽幅高亮、灵活的分类树可视化，以及支持内嵌表格、枚举列表和代码块的多栏布局。通过采用清晰的关注点分离原则并在kt命名空间下实施一致的命名规范，本框架将视觉样式从装饰性附加组件转化为可复现、可扩展的科学交流基础构件，从而提升文章、海报和演示文稿在清晰度、可移植性与创作效率方面的表现。