tutor

Orchestrate multi-stage learning pipelines from research sources into structured curricula.

9|Updated Jul 1, 2026
One-click install
npx skills add https://github.com/Agents4Academia-AI/UReKA --skill tutor-agents4academia-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: tutor
Source: https://github.com/Agents4Academia-AI/UReKA/tree/main/.claude/skills/tutor
Command: npx skills add https://github.com/Agents4Academia-AI/UReKA --skill tutor-agents4academia-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the challenge of unstructured self-directed learning by providing a structured, session-based curriculum that bridges the gap between raw research sources and deep conceptual mastery.

Core Features & Use Cases

  • Session-Based Learning: Breaks down large subjects into manageable, scheduled hour-blocks with clear reading lists and teaching modules.
  • Adaptive Mastery Tracking: Uses spaced-repetition flashcards and Bloom-level questioning to verify knowledge and track progress.
  • Personal Knowledge Integration: Encourages the ingestion of research sources into a personal knowledge base, ensuring that learning is grounded in your own annotated materials.

Quick Start

Run the tutor skill for your machine learning course by typing /tutor machine-learning to begin your next scheduled session.

Frequently Asked Questions about tutor

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

FAQPage Schema
How do I structure self-directed learning from raw research sources?

To structure self-directed learning, this skill synthesizes raw research sources into scheduled, session-based curricula, breaking complex topics into manageable hour-blocks with clear reading lists and teaching modules.

How does adaptive mastery tracking work for complex topics?

Adaptive mastery tracking works by using spaced-repetition flashcards and Bloom-level questioning to verify knowledge, tracking your conceptual progress and updating your personal research database after each session.

Can I integrate my own annotated materials into an AI-driven curriculum?

Yes, you can integrate your own annotated materials by ingesting research sources into a personal knowledge base, ensuring that your scheduled learning and adaptive testing are grounded in your local files.

Do I need local file system access to generate spaced-repetition flashcards?

Yes, local file system access is required to read course modules, track learning progress, promote library resources, and manage knowledge audit updates across your personal research databases.

What's the best way to start a scheduled coaching session for a new subject?

The best way to start a scheduled coaching session is to invoke the skill with your target subject, which triggers the pipeline to read your local course modules and begin the next scheduled hour-block.