deeptutor

Transforms documents into knowledge-graph-backed tutoring sessions with hybrid retrieval and question generation.

32|4|Updated Feb 15, 2026
One-click install
npx skills add https://github.com/ndpvt-web/deeptutor-claude-skill --skill deeptutor-ndpvt-web
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deeptutor
Source: https://github.com/ndpvt-web/deeptutor-claude-skill
Command: npx skills add https://github.com/ndpvt-web/deeptutor-claude-skill --skill deeptutor-ndpvt-web

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires networkx, and includes scripts (resource) components.

What problem does it solve? Studying dense PDFs, textbooks, and papers is slow and passive; this Skill turns documents into an interactive tutoring environment with a searchable knowledge base, entity-relationship knowledge graph, step-by-step problem solving, and practice question generation. ## Core Features & Use Cases - Knowledge Base Initialization: Chunks documents and builds a NetworkX knowledge graph of concepts, definitions, theorems, and their relationships. - Dual-Loop Problem Solving: Separates an Analysis Loop (targeted hybrid retrieval with BM25 plus graph expansion) from a Solve Loop (step-by-step reasoning with citations). - Question Generation & Guided Learning: Creates difficulty-calibrated practice questions grounded in document content and teaches topics along prerequisite-aware learning paths. - Deep Research Reports: Decomposes a topic into subtopics and produces multi-section cited academic reports. - Use Case: Attach a machine learning textbook, ask to build a knowledge base, then request "quiz me on backpropagation at medium difficulty" or "explain gradient descent step by step with citations." ## Quick Start Ask Claude to use deeptutor to create a knowledge base from your attached PDF and then explain a concept from it step by step.

Frequently Asked Questions about deeptutor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a knowledge base from a PDF for studying?▼

Extract the document text, create a knowledge base with kb_manager.py, split the text into 500-1000 word chunks, then extract entities and relationships into a NetworkX knowledge graph with graph_builder.py. The skill's SKILL.md workflow orchestrates each step.

What is hybrid retrieval with BM25 and knowledge graphs?▼

Hybrid retrieval combines BM25 keyword scoring over document chunks with graph expansion that finds related entities and boosts chunks mentioning them. Scores are fused with a configurable alpha weight, defaulting to 0.7 keyword and 0.3 graph.

What dependencies does the DeepTutor skill require?▼

The skill requires Python 3.9 or later and a single external package, networkx, installed via pip install networkx. All other functionality uses the Python standard library plus Claude's native reasoning.

Can I generate practice questions from my own textbook?▼

Yes, after building a knowledge base from the textbook, the skill retrieves relevant chunks and graph context, then generates easy, medium, or hard multiple-choice or written questions grounded in the actual document content with explanations and source references.

What are the limitations compared to the original DeepTutor platform?▼

This skill captures roughly 70% of the original DeepTutor's features, replacing its FastAPI and Next.js infrastructure with three Python scripts and Claude's native reasoning. It lacks the original's database, web UI, and multi-provider LLM support.