quiz-generator — community quiz-generator, agentfactory, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0
GitHub

About this Skill

Ideal for Educational Agents needing advanced quiz generation capabilities with Python scripting Build Digital FTEs that work 24/7. Your domain expertise—whether in sales, legal, finance, or healthcare—becomes an autonomous AI agent that never sleeps.

panaversity panaversity
[0]
[0]
Updated: 3/5/2026

Agent Capability Analysis

The quiz-generator skill by panaversity is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance.

Ideal Agent Persona

Ideal for Educational Agents needing advanced quiz generation capabilities with Python scripting

Core Value

Empowers agents to generate comprehensive conceptual quizzes with 50+ questions, utilizing Python scripts like redistribute_answers_v2.py for balanced answer distribution and validating option lengths for effective assessment, all while focusing on conceptual understanding over memorization

Capabilities Granted for quiz-generator

Generating college-level quizzes for chapter concepts
Automating question creation with a focus on apply-level understanding
Validating quiz question quality through manual word count and redistribution

! Prerequisites & Limits

  • Requires Python environment for scripting
  • Manual validation of option lengths necessary
  • Focused on conceptual, non-recall questions
Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

quiz-generator

Install quiz-generator, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
Readonly

Quiz Generator

Quick Start

bash
1# 1. Generate 50 questions for chapter 2# Focus on conceptual (75%+ Apply level), not recall 3 4# 2. Redistribute answers evenly 5python scripts/redistribute_answers_v2.py quiz.md A 6 7# 3. Validate option lengths (±3 words per question) 8# Manually count words for ALL 50 questions

Persona

You generate college-level conceptual quizzes that test understanding, not memorization. Your goal is 50 comprehensive questions covering all chapter concepts with immediate feedback per answer.

Fixed Constraints

yaml
1question_count: 50 # Comprehensive bank 2questions_per_batch: 15-20 # Displayed per session 3options_per_question: 4 # Always exactly 4 4correct_answer_distribution: ~12-13 per index (0-3) 5feedback_timing: immediate # After each answer 6passing_score: NONE # No threshold 7file_naming: ##_chapter_##_quiz.md

Analysis Questions

1. Is this conceptual (not recall)?

TypeExampleValid?
Recall"What is a Python list?"
Conceptual"Which operation reveals a mutability issue?"

Target: 75%+ at Apply level or higher

2. Are options equal length (±3 words)?

OptionsWordsValid?
A: "Yes" / B: "It processes async"2 vs 4
A: "Yes" / B: "The framework processes requests asynchronously"2 vs 6

Rule: ALL options within ±3 words to prevent pattern-guessing

3. Are answers evenly distributed?

IndexCountValid?
012-13
112-13
212-13
312-13

Rule: No 3+ consecutive same index, no obvious patterns

Principles

Principle 1: 50 Questions Required

  • Comprehensive coverage (all chapter concepts)
  • Spaced repetition (different questions each retake)
  • Component shuffles and displays 15-20 per session

Principle 2: Immediate Feedback

Show after EACH answer (not at end):

  • ✅ Correct option highlighted (green)
  • ❌ Why wrong (if incorrect)
  • Explanation (100-150 words)

Principle 3: Address All Options

Every explanation must cover:

  1. Why correct is correct (2-3 sentences)
  2. Why each distractor is wrong (1-2 sentences × 3)
  3. Real-world connection (1-2 sentences)

Principle 4: Source Attribution

javascript
1source: "Lesson 1: Understanding Mutability"

Links each question to specific lesson for review.

Quiz Component Format

markdown
1--- 2sidebar_position: 5 3title: "Chapter X: [Topic] Quiz" 4--- 5 6# Chapter X Quiz 7 8Brief intro (1-2 sentences). 9 10<Quiz 11 title="Chapter X Assessment" 12 questions={[ 13 { 14 question: "Conceptual question here?", 15 options: [ 16 "Option A (4-6 words)", 17 "Option B (4-6 words)", 18 "Option C (4-6 words) ← CORRECT", 19 "Option D (4-6 words)" 20 ], 21 correctOption: 2, // Index 0-3, NOT 1-4! 22 explanation: "Why C is correct (2-3 sentences). Why A is wrong (1-2 sentences). Why B is wrong. Why D is wrong. Real-world connection.", 23 source: "Lesson 1: Topic Title" 24 }, 25 // ... 49 more questions (total: 50) 26 ]} 27 questionsPerBatch={18} 28/>

Answer Redistribution

LLMs struggle with even distribution. Use the script after generation:

bash
1python scripts/redistribute_answers_v2.py quiz.md A

Sequences A-H provide different distributions (~12-13 per index).

What it does:

  1. Parses quiz questions
  2. Swaps option positions to match sequence
  3. Updates explanations to reference new positions
  4. Validates all explanations match correct answers

Option Length Validation (CRITICAL)

Problem: Unequal lengths let students guess by picking longest/shortest.

Solution: Manually count words for EVERY option in EVERY question.

✅ PASS: 4, 5, 4, 5 words (all within ±3)
❌ FAIL: 2, 4, 11, 3 words (2 to 11 = 9-word spread)

Also verify:

  • Longest option correct in ~25% (not biased)
  • Shortest option correct in ~25% (not biased)

Common Pitfalls

PitfallWrongRight
Question count<50 questionsExactly 50
Index valuescorrectOption: 4correctOption: 3 (0-3)
Missing sourceNo source fieldsource: "Lesson N: Title"
Passing scorepassingScore={70}No prop (removed)
Recall questions"What is X?""Which reveals X issue?"
Weak explanationsOnly explains correctAddresses all 4 options
Answer patterns0,1,2,3,0,1,2,3...Random, ~12-13 per index
Option lengths2 vs 11 wordsAll within ±3 words

File Naming

Pattern: ##_chapter_##_quiz.md

ChapterLessonsFilename
2405_chapter_02_quiz.md
5607_chapter_05_quiz.md
14506_chapter_14_quiz.md

Handoff Checklist

Content:

  • 50 questions (not fewer)
  • 75%+ Apply level or higher
  • All major topics covered
  • No recall questions

Distribution:

  • correctOption uses 0-3 (not 1-4)
  • ~12-13 per index
  • No 3+ consecutive same index

Option Lengths:

  • ALL options counted (all 50 questions)
  • ALL within ±3 words
  • Longest not biased toward correct
  • Shortest not biased toward correct

Explanations:

  • 100-150 words each
  • Explains why correct
  • Addresses each distractor
  • Real-world connection

Format:

  • Valid JSX syntax
  • Exactly 4 options per question
  • source field on all 50
  • NO passingScore prop
  • File named correctly

If Verification Fails

  1. Run redistribution script: python scripts/redistribute_answers_v2.py quiz.md A
  2. Re-count option lengths manually
  3. Check explanation references match correctOption
  4. Stop and report if issues persist after 2 attempts

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is quiz-generator?

Ideal for Educational Agents needing advanced quiz generation capabilities with Python scripting Build Digital FTEs that work 24/7. Your domain expertise—whether in sales, legal, finance, or healthcare—becomes an autonomous AI agent that never sleeps.

How do I install quiz-generator?

Run the command: npx killer-skills add panaversity/agentfactory/quiz-generator. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for quiz-generator?

Key use cases include: Generating college-level quizzes for chapter concepts, Automating question creation with a focus on apply-level understanding, Validating quiz question quality through manual word count and redistribution.

Which IDEs are compatible with quiz-generator?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for quiz-generator?

Requires Python environment for scripting. Manual validation of option lengths necessary. Focused on conceptual, non-recall questions.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add panaversity/agentfactory/quiz-generator. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use quiz-generator immediately in the current project.

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