Quiz Generator Skill

Generate multiple-choice questions (MCQs) with answers for chapter assessment.

Purpose

This skill creates quiz questions based on chapter content to assess reader comprehension. Questions cover key concepts, code understanding, and practical application.

Input Requirements

json

{
  "content": "string",              // Chapter content (MDX/Markdown)
  "chapter_id": "string",           // Chapter identifier
  "num_questions": "number",        // Number of questions (default: 5)
  "difficulty_mix": {               // Distribution of difficulty
    "easy": 0.2,
    "medium": 0.5,
    "hard": 0.3
  },
  "question_types": [               // Types to include
    "concept",                      // Theoretical understanding
    "code",                         // Code comprehension
    "application",                  // Practical scenarios
    "troubleshooting"               // Debug/fix scenarios
  ],
  "include_explanations": "boolean" // Add answer explanations
}

Output Format

json

{
  "chapter_id": "string",
  "quiz_version": "string",
  "questions": [
    {
      "id": "string",
      "type": "concept|code|application|troubleshooting",
      "difficulty": "easy|medium|hard",
      "question": "string",
      "code_snippet": "string|null",
      "options": [
        {"id": "A", "text": "string"},
        {"id": "B", "text": "string"},
        {"id": "C", "text": "string"},
        {"id": "D", "text": "string"}
      ],
      "correct_answer": "A|B|C|D",
      "explanation": "string",
      "related_section": "string"
    }
  ],
  "metadata": {
    "generated_at": "ISO timestamp",
    "source_chapter": "string",
    "total_questions": "number"
  }
}

Example Usage

CLI

bash

claude-code skill quiz-generator --input chapter.mdx --num-questions 5 --output quiz.json

API

python

from specify.skills import QuizGenerator

generator = QuizGenerator()
quiz = generator.generate({
    "content": chapter_content,
    "chapter_id": "week-1-intro",
    "num_questions": 5,
    "difficulty_mix": {"easy": 0.2, "medium": 0.6, "hard": 0.2},
    "question_types": ["concept", "code", "application"],
    "include_explanations": True
})

for q in quiz["questions"]:
    print(f"Q: {q['question']}")
    print(f"A: {q['correct_answer']} - {q['explanation']}")

Question Generation Guidelines

Concept Questions (Theoretical)

•Test understanding of definitions and relationships
•Avoid trivial recall; focus on comprehension
•Include "why" questions, not just "what"

Example:

code

What is the primary advantage of ROS2's use of DDS over ROS1's custom middleware?
A) Lower memory usage
B) Built-in real-time and multi-platform support [CORRECT]
C) Simpler API
D) Faster compilation times

Code Questions (Comprehension)

•Show code snippets and ask about behavior
•Test ability to read and understand code
•Include output prediction questions

Example:

python

# Given this code:
self.publisher_ = self.create_publisher(String, 'hello_topic', 10)

code

What does the number '10' represent in this publisher creation?
A) Message size in bytes
B) Queue depth for messages [CORRECT]
C) Publish frequency in Hz
D) Topic priority level

Application Questions (Practical)

•Present real-world scenarios
•Ask for best approach or tool selection
•Test decision-making ability

Troubleshooting Questions

•Show error messages or broken code
•Ask to identify the problem
•Test debugging skills

Quality Criteria

Questions Must:

•Be clearly answerable from chapter content
•Have exactly one correct answer
•Include plausible distractors (wrong answers)
•Avoid "all of the above" or "none of the above"
•Not use negatives ("Which is NOT...")

Distractors Must:

•Be plausible but clearly wrong
•Address common misconceptions
•Be similar in length to correct answer
•Not be obviously absurd

Integration

This skill:

•Powers the <ChapterQuiz /> component
•Is called by chapter-writer skill
•Feeds into progress tracking system

Example Output

json

{
  "chapter_id": "week-1-intro",
  "quiz_version": "1.0",
  "questions": [
    {
      "id": "q1-ros2-architecture",
      "type": "concept",
      "difficulty": "easy",
      "question": "What middleware does ROS2 use for communication between nodes?",
      "code_snippet": null,
      "options": [
        {"id": "A", "text": "MQTT"},
        {"id": "B", "text": "DDS (Data Distribution Service)"},
        {"id": "C", "text": "REST APIs"},
        {"id": "D", "text": "WebSockets"}
      ],
      "correct_answer": "B",
      "explanation": "ROS2 is built on top of DDS, an industry-standard middleware for real-time distributed systems. This provides features like QoS policies, discovery, and security.",
      "related_section": "Theory: ROS2 Architecture"
    },
    {
      "id": "q2-publisher-code",
      "type": "code",
      "difficulty": "medium",
      "question": "In the following code, what does `timer_period = 1.0` control?",
      "code_snippet": "self.timer = self.create_timer(timer_period, self.timer_callback)",
      "options": [
        {"id": "A", "text": "How long the node runs before shutting down"},
        {"id": "B", "text": "The interval between callback function executions"},
        {"id": "C", "text": "The timeout for receiving messages"},
        {"id": "D", "text": "The message queue timeout"}
      ],
      "correct_answer": "B",
      "explanation": "The timer_period parameter sets how frequently (in seconds) the timer_callback function is called. With 1.0, the callback runs every second.",
      "related_section": "Task 2: Create Your First Node"
    }
  ]
}