Skills

Generating Practice Questions

Generate educational practice questions from lecture notes to test student understanding.

Install

npx skills add datawhalechina/agent-skills-with-anthropic --skill generating-practice-questions -g -a claude-code -y
Category
Testing
Updated
2mo ago
License
See repository
Context cost
Lightabout 1,318 tokens
Runs scripts
No, instructions only

What it does

Generate educational practice questions from lecture notes to test student understanding. Use when users request practice questions, exam preparation materials, study guides, or assessment items based on lecture content.

Practice Question Generator

Generate comprehensive practice questions from lecture notes to test student understanding of learning objectives and key concepts.

Input

Supported formats: LaTeX (.tex), PDF, Markdown (.md), plain text (.txt)

  • PDF: Use pdfplumber for text extraction

  • LaTeX: Read as text, strip preamble (everything before \begin{document}), preserve math environments ($...$, \[...\], \begin{equation}, etc.)

  • Markdown/Text

Content to extract:

  1. Learning objectives - Usually at beginning: "After this lecture, you should be able to..." or may be in section: "Learning Outcomes","Objectives", "Goals". If absent, derive from main topics.
  2. Main topics - Section headings, bold terms, definitions, algorithms.
  3. Examples - Use for realistic scenarios in questions.

Question Structure

Generate questions in this order:

  1. True/False (one per learning objective, or 3-5 if no objectives)
  2. Explanatory Questions (3-5 covering main topics)
  3. Coding Question (1 algorithm implementation or concept simulation)
  4. Use Case (1 realistic application)

For each question type, follow guidelines below, and never include answer key.

Question Guidelines

Type 1: True/False

Test factual understanding and common misconceptions.

Coverage:

  • One per learning objective, or 3-5 covering main topics if no objectives

Difficulty progression:

  • Start with 1-2 simple definitional questions
  • Include 2-3 reasoning-based questions requiring concept application or testing relationships between concepts

Quality criteria:

  • Unambiguous with one correct interpretation
  • Clear language without complex nested clauses
  • Answer directly found in lecture notes
  • Wrong answer reveals common misconception

Examples:

Read the whole SKILL.md on GitHub

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