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Agent Skill · 待分类

course-description-analyzer(课程描述分析器)

course-description-analyzer 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。

course-description-analyzer 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证为 MIT,第三方扫描已通过,按安装量在待分类类的 11,209 个 Skill 里排第 4,778。

总安装 679周安装 28GitHub Stars 65下载 222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
MIT

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:course-description-analyzer(课程描述分析器)
来源仓库:https://github.com/dmccreary/claude-skills
仓库路径:skills/course-description-analyzer
安装命令:
npx skills add https://github.com/dmccreary/claude-skills --skill course-description-analyzer
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/dmccreary/claude-skills --skill course-description-analyzer

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

course-description-analyzer 用于分析和优化课程描述质量,确保其包含足够元素以支撑后续学习图谱生成,适合在 Codex、Claude、Cursor、Gemini CLI 中需要提升教学内容完整性时使用。

它检查文档是否存在,并根据情况进入创建或完善流程,目标是产出覆盖 200+ 概念的高质量描述。通过比对 Bloom's Taxonomy 学习成果标准,Agent 可验证内容对齐度、知识覆盖广度及结构合理性。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。

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/course-description-analyzer

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 course-descrip…;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

course-description-analyzer 怎么安装?

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

course-description-analyzer 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。

course-description-analyzer 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。

course-description-analyzer 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

course-description-analyzer 用的人多吗?

公开数据是累计安装 679 次,近一周安装 28 次,下载 222 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。

course-description-analyzer 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
course-description-analyzer

课程描述分析器 · 本页

67965只读MIT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

Course Description Analyzer

Overview

This Anthropic Claude Skill is the first step in the process of generating an intelligent textbook. The next Skill is the 'learning-graph-generator` Skill.

Analyze or create high-quality course descriptions that contain all necessary elements for generating comprehensive learning graphs with 200+ concepts. Check the /docs/course-description.md file for completeness, quality, and alignment with 2001 Bloom's Taxonomy learning outcomes.

Workflow Decision Tree

Start by checking if /docs/course-description.md exists:

  • File does not exist → Follow Creation Workflow (Step 1)
  • File exists → Follow Analysis Workflow (Step 2)

Tell the user that they are running Version 0.03 of the Course Description Analyzer Skill.

Step 1: Course Description Creation

Use this workflow when /docs/course-description.md does not exist.

1.1 Gather Course Information

Ask the user the following questions sequentially (not all at once):

  1. What is the title of the course?
  2. What is the target audience of the course?

- Options: elementary, junior high, high school, college undergraduate, graduate students, adult continuing education, professional development, or other

  1. What are the prerequisites for this course?

- If none, explicitly state "None"

  1. What are the main subjects/topics covered by this course?

- Request a list of major topics

  1. What are the learning outcomes organized by the 2001 Bloom's Taxonomy?

- Explain that after this course, students will be able to demonstrate competencies at each level: - Remember: Retrieve, recognize, and recall relevant knowledge - Understand: Construct meaning from instructional messages - Apply: Carry out or use procedures in given situations - Analyze: Break material into parts and determine relationships - Evaluate: Make judgments based on criteria and standards - Create: Put elements together to form coherent wholes; includes capstone projects

1.2 Generate Course Description

Use the template from assets/course-description-template.md and populate it with the user's responses. Create the file at /docs/course-description.md.

Ensure the generated file includes:

  • Clear course title
  • Target audience specification
  • Prerequisites (or "None")
  • Comprehensive list of main topics
  • Section for topics NOT covered (to set boundaries)
  • Detailed learning outcomes organized by all six Bloom's Taxonomy levels
  • Descriptive text explaining why the course is important

1.3 After Creation

After creating the file, automatically proceed to Step 2 (Analysis Workflow) to validate the newly created course description and provide a quality score.

Step 2: Course Description Analysis

Use this workflow when /docs/course-description.md already exists.

2.1 Read the Course Description

Read /docs/course-description.md and analyze its contents against the quality criteria.

2.2 Course Description Quality Scoring System

Evaluate the course description using this 100-point scoring system:

ElementPointsCriteria
Title5Clear, descriptive course title present
Target Audience5Specific audience identified (e.g., "college undergraduate")
Prerequisites5Prerequisites listed or explicitly stated as "None"
Main Topics Covered10Comprehensive list of topics (ideally 5-10 topics)
Topics Excluded5Clear boundaries set for what's NOT covered
Learning Outcomes Header5Clear statement: "After this course, students will be able to..."
Remember Level10Multiple specific outcomes for remembering/recalling
Understand Level10Multiple specific outcomes for understanding/explaining
Apply Level10Multiple specific outcomes for applying/using
Analyze Level10Multiple specific outcomes for analyzing/breaking down
Evaluate Level10Multiple specific outcomes for evaluating/judging
Create Level10Multiple specific outcomes for creating/synthesizing; includes capstone ideas
Descriptive Context5Additional context about course importance, relevance, or value

Scoring Guidelines:

  • Award full points if element is complete and high-quality
  • Award partial points if element is present but incomplete or vague
  • Award 0 points if element is missing
  • For Bloom's Taxonomy levels, require at least 3 specific, actionable outcomes for full points

2.3 Gap Analysis

Identify missing or weak elements:

  • List each element that scored less than full points
  • Explain what is missing or insufficient
  • Indicate how the absence impacts learning graph generation

2.4 Improvement Suggestions

Provide specific, actionable recommendations:

  • For missing elements: Suggest what should be added
  • For weak elements: Provide examples of how to strengthen them
  • For Bloom's Taxonomy outcomes: Recommend specific verbs and topics
  • Prioritize suggestions that will have the most impact on reaching the goal of generating 200 concepts

2.5 Course Description Assessment Report

Use mkdir -p docs/learning-graph to create a learning-graph directory in the docs directory.

Generate a comprehensive quality report on the course description and write it to docs/learning-graph/course-description-assessment.md

  1. Overall Score: X/100
  2. Quality Rating:

- 90-100: Excellent - Ready for learning graph generation - 75-89: Good - Minor improvements recommended - 60-74: Adequate - Several improvements needed - 40-59: Fair - Significant gaps to address - 0-39: Poor - Major revision required

  1. Detailed Scoring Breakdown: Show points earned for each element
  2. Gap Analysis: List of missing or weak elements
  3. Improvement Suggestions: Prioritized recommendations
  4. Next Steps:

- If score ≥ 85: Ready to proceed with learning graph generation - If score < 85: Recommend addressing specific gaps before generating learning graph

2.6 Update Course Description Metadata

In this section NAME is the name of the course taken from the course description. QUALITY_SCORE is the score you computed for the course description.

If it does not exist, add the following yml metadata at the top of the docs/course-description.md file:

---
title: Course Description for Course NAME
description: A detailed course description for NAME including overview, topics covered and learning objectives in the format of the 2001 Bloom Taxonomy
quality_score: QUALITY_SCORE
---

2.7 Concept Generation Readiness

Assess whether the course description contains sufficient detail to generate 200 concepts:

  • Evaluate topic breadth and depth
  • Check if Bloom's Taxonomy outcomes suggest diverse concept types
  • Estimate potential concept count based on current content
  • Recommend additions if concept generation may fall short

Add course-description.md and and the course-description-assessment.md to mkdocs.yml Navigation

After the course-description.md file has been added to the /docs direction, ask the user if the new file should be added to the mkdocs.yml file. If the answer is yes, place the new file after the about.md file.

nav:
   ...
   About: about.md
   Course Description: course-description.md
   ...
   Learning Graph:
      Course Description Assessment: learning-graph/course-description-assessment.md

Next Step

For all users with a score over 85, ask if the learning-graph-generator skill should be run next.

Best Practices

When using this skill:

  1. Be thorough: Don't skip Bloom's Taxonomy levels—all six are essential for comprehensive learning
  2. Be specific: Vague outcomes like "understand the material" won't support quality learning graphs
  3. Use action verbs: Each outcome should start with a measurable verb (list, explain, apply, analyze, evaluate, design, etc.)
  4. Think concepts: Each topic and outcome should suggest multiple learnable concepts
  5. Set boundaries: Topics excluded are as important as topics covered for scope management

Resources

assets/

  • course-description-template.md: Template structure for creating new course descriptions with all required sections and Bloom's Taxonomy framework

平台分布

Codex

29.17%
按下载量换算65

windsurf

23.56%
按下载量换算52

Claude Code

17.12%
按下载量换算38

OpenCode

12.57%
按下载量换算28

Gemini CLI

8.72%
按下载量换算19

Antigravity

3.52%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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。

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