quiz-generator — community quiz-generator, agentfactory, community, ide skills

v1.0.0

About this Skill

Ideal for Educational Agents and Domain Experts needing automated college-level conceptual quiz generation with Python scripting capabilities. Generate 50-question interactive quizzes using the Quiz component with randomized batching. Use when creating end-of-chapter assessments. Displays 15-20 questions per session with immediate feedback.

panaversity panaversity
[0]
[0]
Updated: 3/9/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 7/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Locale and body language aligned
Review Score
7/11
Quality Score
30
Canonical Locale
en
Detected Body Locale
en

Ideal for Educational Agents and Domain Experts needing automated college-level conceptual quiz generation with Python scripting capabilities. Generate 50-question interactive quizzes using the Quiz component with randomized batching. Use when creating end-of-chapter assessments. Displays 15-20 questions per session with immediate feedback.

Core Value

Empowers agents to generate comprehensive conceptual quizzes with 75%+ Apply level questions, utilizing Python scripts like redistribute_answers_v2.py for even answer redistribution and validating option lengths with ±3 words per question, ensuring in-depth understanding rather than mere memorization.

Ideal Agent Persona

Ideal for Educational Agents and Domain Experts needing automated college-level conceptual quiz generation with Python scripting capabilities.

Capabilities Granted for quiz-generator

Generating 50 comprehensive questions for chapter concepts
Redistributing answers evenly across quizzes using redistribute_answers_v2.py
Validating option lengths for all questions to ensure consistency

! Prerequisites & Limits

  • Requires Python environment for script execution
  • Manual word count needed for validating option lengths
  • Focus on conceptual questions may not suit all educational needs

Why this page is reference-only

  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

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 and Domain Experts needing automated college-level conceptual quiz generation with Python scripting capabilities. Generate 50-question interactive quizzes using the Quiz component with randomized batching. Use when creating end-of-chapter assessments. Displays 15-20 questions per session with immediate feedback.

How do I install quiz-generator?

Run the command: npx killer-skills add panaversity/agentfactory. 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 50 comprehensive questions for chapter concepts, Redistributing answers evenly across quizzes using redistribute_answers_v2.py, Validating option lengths for all questions to ensure consistency.

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 script execution. Manual word count needed for validating option lengths. Focus on conceptual questions may not suit all educational needs.

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. 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.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

quiz-generator

Install quiz-generator, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

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

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