concept-classifier_skill

This skill helps students learn classification across subjects by presenting scenario based questions with multiple choices and instant explanations.
  • Python

14

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill dmccreary/claude-skills --skill concept-classifier

  • skill.md9.4 KB

Overview

This skill builds an interactive classification quiz MicroSim using p5.js so students read scenarios and choose the correct category from multiple-choice options. It separates content into a data.json file for simple editing and supports randomized questions, hints, automatic explanations, and score tracking. The format is suited to teaching pattern recognition and concept identification across any subject area.

How this skill works

The MicroSim loads a data.json file that defines the quiz title, configuration, scenarios, options, correct answers, hints, and explanations. The p5.js sketch renders scenarios, presents multiple-choice buttons, tracks score and progress, and shows immediate feedback with an animated mascot and end-of-quiz performance summary. Hints reduce points but aid learners; question order is randomized and a subset is selected per quiz.

When to use it

  • Teaching students to identify types or categories (biases, literary devices, reaction types)
  • Practicing classification of real-world examples (taxonomic groups, historical periods)
  • Training pattern recognition (design patterns, musical forms, art movements)
  • Formative assessment with immediate explanations and score tracking
  • Creating practice sets that instructors can edit without changing code

Best practices

  • Write clear, specific scenarios that demonstrate a single category
  • Provide plausible distractors that reflect common misconceptions
  • Keep scenario length to 2–4 sentences for readability on the canvas
  • Mix difficulty levels and include 15–30 scenarios so randomization is meaningful
  • Write concise explanations that point to the key features distinguishing the correct category

Example use cases

  • Cognitive bias quiz where students identify the bias in short vignettes
  • Literary device recognizer presenting passages for students to classify
  • Chemical reaction classifier that asks students to label reaction types
  • Historical era matcher where events or artifacts are assigned to periods
  • Design pattern identifier that shows code snippets or scenarios to classify

FAQ

Edit the scenarios array in data.json. Each item needs id, scenario, options, correctAnswer, explanation, and hint fields.

Can I change the number of questions per quiz?

Yes. Adjust config.questionsPerQuiz in data.json or change the slice count where scenarios are selected in the JavaScript.

Does the quiz support accessibility?

Yes. The implementation includes descriptive text for screen readers and uses clear labels; further accessibility tweaks can be added in the HTML wrapper.

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