tutor-de-skills

Agent Tutor turns Claude Code into a tutor that requires learners to explain, apply, and transfer a concept before marking it understood. Zero-hint quizzes expose weak recall, while FSRS schedules review separately for each concept. Progress, misconceptions, and session history persist in local Markdown files, and lessons can be grounded in PDFs, documents, web pages, or source code.

This Claude Code skill reviews an undergraduate thesis through six weighted dimensions: topic and workload, methodology, data and results, discussion and argument, writing and structure, and references and academic practice. It scans the document, confirms checkpoints, performs chapter-level review by discipline, and produces a seven-part report. Selectable-text PDF, DOC, or LaTeX files are supported; scanned pages need OCR. The score is calibrated for undergraduate work and does not replace a supervisor, formal plagiarism check, or graduate-level review.

cognitive-learning-canvas is a Chinese-language prompt framework for Claude, ChatGPT, Gemini, and similar assistants. It organizes difficult courses, papers, documents, or video transcripts into seven Obsidian Canvas layers: schema anchor, concrete example, terms, mechanism chain, self-test, deeper understanding, and a one-line close. A core metaphor and four-question test support pre-reading and concept mapping; it is not a replacement for the source or a step-by-step tutorial.

Give the skill one focused concept—such as an agent, RAG, or chain-of-thought—and it produces a self-contained HTML lesson with sourced definitions, plain-language explanation, a continuing product example, practice questions, and an interactive demo. It is designed mainly for AI product-manager training and technical education, using a fixed four-step creation process so separate lessons keep a consistent structure.