dsh-course-logic-extractor

You have a full set of lecture notes, slides, subtitles, or a paper PDF in hand, and the real headache is not the volume of content but the invisible design logic behind it: what is taught first, what comes next, why each piece sits where it does, and how the parts chain together. dsh-course-logic-extractor tackles exactly this. It reads the materials, reconstructs the author's pedagogical or research intent, and delivers a self-consistent logic-chain analysis report, an actionable learning roadmap, and a set of flow-canvas files so you can see the whole map before turning chapter one.

Three entry modes keep it flexible: point it at a folder of materials for a straight analysis; feed it a paper and it will unfold a dual lens of research logic and learning logic; or, if you have nothing ready, it runs an iterative confirmation loop with you — first breaking the topic into a capability-point tree with dependencies and mastery criteria, then assembling a resource list — and only moves on after you explicitly say you are fully settled. The material pipeline covers high-resolution PDF rendering, GLM-OCR transcription, quality reconciliation, and archiving, all backed by unit tests and CI.

It is built for graduate students wrestling with a course, self-learners mapping a new field, instructors who want to reverse-engineer a syllabus for their own teaching design, and researchers who want to pull both the argument and the learning path out of a single paper. In short: understand the skeleton before filling in the flesh.