agentleFS
SkillMedevSkillMedev/course-creator-launch-system/skills/quiz-generator/SKILL.md

quiz-generator

Skill1 starsChanged 4 months agoMITView on GitHub

Writes quizzes and assessments with a stated Bloom's-level distribution, misconception-based distractors, and an answer key with rationales - plus a summary table of level, type, and points per question. Use when someone asks "write a quiz on...", "make a 10-question test for chapter 5", "generate review questions", or "check these multiple-choice questions for quality". Do NOT use for building the grading rubric for an essay or project - use rubric-builder instead; for designing the lesson the quiz sits inside, use lesson-plan-builder; for opinion or research surveys rather than knowledge assessment, use survey-designer.

13 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use chapter-content-generator, course-description-analyzer and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • vishalsachdevSkill

    chapter-content-generator

    This skill generates comprehensive chapter content for intelligent textbooks after the book-chapter-generator skill has created the chapter structure. Use this skill when a chapter index.md file exists with title, summary, and concept list, and detailed educational content needs to be generated at the appropriate reading level with rich non-text elements including diagrams, infographics, and MicroSims. (project, gitignored)

    Also in 4 projects that use this

  • vishalsachdevSkill

    course-description-analyzer

    This skill analyzes or creates course descriptions for intelligent textbooks by checking for completeness of required elements (title, audience, prerequisites, topics, Bloom's Taxonomy outcomes) and providing quality scores with improvement suggestions. Use this skill when working with course descriptions in /docs/course-description.md that need validation or creation for learning graph generation.

    Also in 4 projects that use this

  • dmccrearySkill

    book-installer

    Installs and configures intelligent-textbook infrastructure - scaffold a brand-new MkDocs Material textbook (init textbook), install any of 41 features (math, mascot, learning graph viewer, Google Analytics GA4, custom 404, kanban board), and generate book metrics. Routes to the appropriate installation guide.

    Also in 3 projects that use this

  • nek1987Skill

    faq-generator

    Generate faq generator operations. Auto-activating skill for Technical Documentation. Triggers on: faq generator, faq generator Part of the Technical Documentation skill category. Use when working with faq generator functionality. Trigger with phrases like "faq generator", "faq generator", "faq".

    Also in 4 projects that use this

  • +8 more from vishalsachdev

The file

We split this skill into the rules it gives an agent

7 rules. 0 are common, 7 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 10 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Do not default to all-recall.

    line 74
  2. Distinctive:

    Do not write filler distractors - every wrong option a student would never choose wastes an opportunity to detect a misconception.

    line 75
  3. Distinctive:

    Do not use true/false on graded summative work.

    line 76
  4. Distinctive:

    Do not let one question test two things at once.

    line 77
  5. Distinctive:

    Do not ship a key without rationales.

    line 78
  6. Distinctive:

    Every MC distractor maps to a named misconception.

    line 83
  7. Distinctive:

    Every correct answer survives the "could a well-prepared student defend a different option?" test.

    line 84

“Common” is measured: kept by at least 6 in 10 of the 10 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Quiz Generator

A well-constructed quiz is a learning event, not just a measuring event. The costly failure this skill prevents is the all-recall quiz with throwaway distractors: it reports high scores while misconceptions calcify undetected, and the teacher learns nothing actionable from the results.

Operating procedure

Step 1: Gather inputs

Collect before writing any question. Where the user cannot answer, use the default and label assumptions as guesses.

  1. Topic and the specific objectives or content covered (required).
  2. Grade or level (required).
  3. Purpose: formative check, unit exam, or review/performance task (default: formative).
  4. Question count and time budget (default: 10 questions; budget roughly 1 minute per multiple-choice item, 3-5 per short answer, 10+ per constructed response).
  5. Known misconceptions in this topic (ask - these become distractors; if none supplied, derive them from typical partial understandings and label them as guesses).
  6. Format constraints: paper vs digital, calculator allowed, open notes.

Step 2: State the Bloom's distribution before writing questions

Bloom's six levels, lower to higher order: Remember, Understand, Apply, Analyze, Evaluate, Create. Declare the target mix first; do not drift toward all-recall by default.

  • Formative quiz: covers Remember through Apply - roughly 40% Remember/Understand, 60% Apply.
  • Unit exam: must reach Analyze and Evaluate - no more than 50% of points on Remember/Understand.
  • Performance/review task: Evaluate and Create dominate.

Red line: if every question is Remember-level, the quiz measures memorization only - rebalance before proceeding.

Step 3: Match question type to level

  • Multiple choice: efficient for Remember and Understand; use sparingly for Apply and above.
  • Short answer: versatile across Apply, Analyze, Evaluate.
  • Constructed response / scenario-based: best for Analyze and above.
  • True/false: low signal - diagnostic pre-checks only, never graded summative work.

Step 4: Write stems, then distractors from misconceptions

Lower-order stems are direct and simple: define, identify, list. Higher-order stems use scenarios, data sets, or documents as stimulus - kept concise and free of culturally specific references that create construct-irrelevant difficulty.

Every multiple-choice distractor must be the answer a student with a specific partial understanding would choose. Rules: the correct answer must be unambiguously correct (if a second option survives a defensible interpretation, rewrite the stem, not the option); no "all of the above" / "none of the above" except in carefully controlled contexts; keep options parallel in length and grammar, since the longest option telegraphs the answer.

Step 5: Build the answer key with rationales

For each question: the correct answer, a one-sentence rationale for why it is correct, and - for multiple choice - the misconception each distractor represents. This is part of the deliverable, not an extra.

Step 6: Assemble and check the summary table

Group questions by cognitive level, labeled. Produce the table (question number, level, type, points) and verify the actual point distribution matches the Step 2 declaration. If it drifted, fix questions, not the declaration.

Worked contrast: distractor quality

Topic: photosynthesis, Understand level.

Bad: "What do plants need for photosynthesis? A) sunlight, water, CO2 B) rocks C) music D) darkness" B, C, D are jokes no partially-informed student would pick; the item measures test-taking, not understanding.

Good: "Where does most of the mass of a growing tree come from? A) carbon dioxide in the air (correct) B) minerals absorbed from the soil C) water pulled up by the roots D) energy from sunlight converted to matter" Distractor analysis: B is the classic "plants eat soil" misconception; C confuses the reactant present in largest volume with the mass source; D reflects the common energy-becomes-matter confusion. A student choosing B tells the teacher exactly what to re-teach.

Deliverable

Produce: (1) the question set grouped and labeled by Bloom's level, with total points stated; (2) the summary table - question number, cognitive level, question type, point value; (3) the answer key with per-question rationale and per-distractor misconception notes. Offer a student-facing version (instructions, no key) and a teacher version as separate documents.

Do NOT

  • Do not default to all-recall; a quiz that never reaches Apply cannot distinguish understanding from memorization.
  • Do not write filler distractors - every wrong option a student would never choose wastes an opportunity to detect a misconception.
  • Do not use true/false on graded summative work; a coin flip scores 50%.
  • Do not let one question test two things at once; a wrong answer becomes undiagnosable.
  • Do not ship a key without rationales; "B" alone forces the teacher to re-derive every answer during grading.

Quality bar

  • The Bloom's distribution was declared before writing and the final table matches it.
  • Every MC distractor maps to a named misconception; no joke options.
  • Every correct answer survives the "could a well-prepared student defend a different option?" test.
  • Stimulus material is concise and construct-relevant.
  • Total points and per-question values are stated and sum correctly.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.