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Agent Skill · 开发

concept-classifier(概念分类器)

concept-classifier 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

concept-classifier 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 19,141。

总安装 291周安装 12GitHub Stars 65下载 95核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:concept-classifier(概念分类器)
来源仓库:https://github.com/dmccreary/claude-skills
仓库路径:skills/concept-classifier
安装命令:
npx skills add https://github.com/dmccreary/claude-skills --skill concept-classifier
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/dmccreary/claude-skills --skill concept-classifier

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

concept-classifier 创建交互式分类测验 MicroSim,训练模式识别与概念归类能力。适用于 Codex、Claude、Cursor、Gemini CLI 中开发 p5.js 驱动的教学模拟程序。学生面对场景描述后选择正确类别,强化认知偏差、逻辑谬误等抽象概念理解。

安装前请确认是否嵌入课堂系统、收集用户答题数据或导出成绩报告。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/concept-classifier

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/dmccreary/claude-skills --skill concept-classi…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

concept-classifier 怎么安装?

在终端执行 npx skills add https://github.com/dmccreary/claude-skills --skill concept-classifier。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

concept-classifier 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

concept-classifier 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

concept-classifier 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

concept-classifier 用的人多吗?

公开数据是累计安装 291 次,近一周安装 12 次,下载 95 次,GitHub 65 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

concept-classifier 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
concept-classifier

概念分类器 · 本页

29165只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Concept Classifier Quiz MicroSim Skill

Overview

This skill creates interactive classification quiz MicroSims using p5.js. Students are presented with scenarios, examples, or descriptions and must classify them into the correct category from multiple choice options. The quiz format is ideal for teaching pattern recognition, concept identification, and categorization skills across any subject domain.

When to Use This Skill

Use this skill when you need to create a quiz where students must:

  • Identify types or categories - e.g., identify which cognitive bias is shown, which logical fallacy is used, which literary device is present
  • Classify examples - e.g., classify animals into taxonomic groups, chemical reactions by type, historical events by era
  • Recognize patterns - e.g., recognize which design pattern is used, which musical form is playing, which art movement a painting belongs to
  • Match scenarios to concepts - e.g., match business scenarios to management theories, symptoms to conditions, code snippets to algorithms

Features

  • Scenario-based questions with detailed descriptions
  • Multiple choice answers (typically 4 options per question)
  • Hint system that reduces points but helps struggling students
  • Automatic explanations shown after each answer
  • Score tracking with visual progress indicator
  • Randomized question selection from a larger pool
  • Encouraging feedback messages for both correct and incorrect answers
  • Animated mascot character that reacts to answers
  • End screen with performance summary and tips
  • Fully configurable via data.json file

Data Structure

All quiz content is stored in a data.json file for easy editing. Here is the required structure:

{
  "title": "Quiz Title Here",
  "description": "Brief description of what this quiz tests",
  "config": {
    "questionsPerQuiz": 10,
    "pointsCorrect": 10,
    "pointsWithHint": 5,
    "scenarioLabel": "SCENARIO",
    "instructionText": "Select the correct category for this scenario",
    "correctAnswerField": "correctAnswer"
  },
  "scenarios": [
    {
      "id": 1,
      "scenario": "Description of the scenario or example to classify...",
      "correctAnswer": "Category Name",
      "options": ["Category Name", "Wrong Option 1", "Wrong Option 2", "Wrong Option 3"],
      "explanation": "Explanation of why this answer is correct...",
      "hint": "A helpful hint for this question..."
    }
  ],
  "encouragingMessages": {
    "correct": [
      "Excellent!",
      "Well done!",
      "Great job!",
      "You got it!",
      "Perfect!"
    ],
    "incorrect": [
      "Not quite—now you know for next time!",
      "Good try! This one is tricky.",
      "Learning from mistakes makes us better!",
      "Keep practicing!",
      "Almost! Now you'll remember it."
    ]
  },
  "categoryDescriptions": {
    "Category Name": "Brief description of this category",
    "Another Category": "Brief description of another category"
  },
  "endScreen": {
    "tipsTitle": "Tips for Success:",
    "tips": [
      "First tip for students...",
      "Second tip for students...",
      "Third tip for students..."
    ],
    "performanceMessages": {
      "excellent": {
        "threshold": 90,
        "message": "Outstanding!",
        "subMessage": "You have excellent classification skills."
      },
      "good": {
        "threshold": 70,
        "message": "Great Job!",
        "subMessage": "You classified most items correctly."
      },
      "fair": {
        "threshold": 50,
        "message": "Good Progress!",
        "subMessage": "Keep practicing to improve."
      },
      "needsWork": {
        "threshold": 0,
        "message": "Keep Learning!",
        "subMessage": "Practice makes perfect."
      }
    }
  }
}

File Structure

Each Concept Classifier MicroSim creates these files:

/docs/sims/$MICROSIM_NAME/
├── index.md           # Documentation page with iframe embed
├── main.html          # HTML wrapper loading p5.js
├── $MICROSIM_NAME.js  # p5.js quiz logic
├── data.json          # Quiz questions and configuration
└── metadata.json      # Dublin Core metadata

Customization Options

Visual Customization

The JavaScript file contains configurable parameters:

// Canvas dimensions
let canvasWidth = 800;
let drawHeight = 480;
let controlHeight = 50;

// Colors (can be customized)
// Drawing area: 'aliceblue' with 'silver' border
// Correct answer: green tones
// Incorrect answer: orange/red tones
// Mascot: pink brain character (can be replaced)

Mascot Character

The default mascot is an animated brain character with three expressions:

  • neutral - default state
  • happy - when answer is correct
  • thinking - when hint is used or answer is incorrect

You can customize or replace the drawMascotCharacter() function to use a different mascot appropriate to your subject domain.

Question Count

By default, 10 questions are randomly selected from the pool. Adjust in the config:

"config": {
  "questionsPerQuiz": 10
}

Or modify in JavaScript:

scenarios = shuffled.slice(0, 10);  // Change 10 to desired number

Example Use Cases

1. Cognitive Bias Quiz (Ethics/Psychology)

Students read scenarios demonstrating cognitive biases and must identify which bias is shown.

2. Logical Fallacy Identifier (Philosophy/Critical Thinking)

Students analyze arguments and identify which logical fallacy is present.

3. Literary Device Recognizer (English/Literature)

Students read passages and identify metaphors, similes, personification, etc.

4. Chemical Reaction Classifier (Chemistry)

Students read reaction descriptions and classify as synthesis, decomposition, single replacement, etc.

5. Historical Era Matcher (History)

Students read about events or artifacts and match them to the correct historical period.

6. Design Pattern Identifier (Computer Science)

Students read code scenarios and identify which software design pattern applies.

7. Musical Form Quiz (Music)

Students listen to or read about musical pieces and identify the form (sonata, rondo, theme and variations, etc.).

8. Art Movement Classifier (Art History)

Students view or read about artworks and classify them into movements (Impressionism, Cubism, etc.).

Implementation Steps

  1. Define your categories - List all possible classification categories (typically 4-8)
  2. Create scenarios - Write 15-30 scenarios, each clearly demonstrating one category
  3. Write explanations - For each scenario, explain why it belongs to that category
  4. Add hints - Provide helpful hints that guide without giving away the answer
  5. Customize messages - Adjust encouraging messages and tips for your subject
  6. Test thoroughly - Ensure all scenarios have correct answers and clear explanations

Best Practices

Writing Good Scenarios

  • Be specific - Scenarios should clearly demonstrate one category
  • Avoid ambiguity - Each scenario should have one clearly correct answer
  • Use realistic examples - Real-world scenarios are more memorable
  • Vary difficulty - Mix easy and challenging scenarios
  • Keep length manageable - Scenarios should fit in the display area (roughly 2-4 sentences)

Writing Good Distractors (Wrong Answers)

  • Make them plausible - Wrong answers should be reasonable alternatives
  • Avoid obviously wrong options - Each option should require thought
  • Use common misconceptions - Include options that represent typical errors
  • Keep similar length - Options should be roughly equal in length

Writing Good Explanations

  • Explain the "why" - Don't just state the answer, explain the reasoning
  • Reference key features - Point out what makes this scenario fit the category
  • Keep it concise - 2-3 sentences is ideal
  • Educational tone - Use this as a teaching moment

Template Files

This skill includes template files in the /templates directory:

  • concept-classifier-template.js - Generalized p5.js quiz logic
  • data-template.json - Example data structure with placeholders
  • main-template.html - HTML wrapper
  • index-template.md - Documentation page template

Bloom's Taxonomy Level

This quiz format primarily addresses Application (Level 3) - students must apply their knowledge of categories to analyze new scenarios they haven't seen before.

Integration with MkDocs

After creating the MicroSim, add it to mkdocs.yml:

nav:
  - MicroSims:
    - Your Quiz Name: sims/your-quiz-name/index.md

Technical Notes

  • Framework: p5.js 1.11.10
  • Responsive: Width-responsive, fixed height
  • Data loading: Uses p5.js loadJSON() in preload()
  • Accessibility: Includes describe() for screen readers
  • Browser support: Modern browsers (Chrome, Firefox, Safari, Edge)

Conclusion

The Concept Classifier skill provides a proven, engaging format for teaching classification and categorization skills. By separating content (data.json) from logic (JavaScript), it's easy to create new quizzes for any subject domain without modifying code.

平台分布

Codex

34.84%
按下载量换算33

Claude

32.56%
按下载量换算31

Cursor

19.93%
按下载量换算19

Gemini CLI

10.14%
按下载量换算10

安全审计

Gen Agent Trust Hub

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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