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Validates or creates a course description for an intelligent textbook, scoring completeness against required elements (title, audience, prerequisites, topics, Bloom's Taxonomy outcomes). Use before running the learning-graph-generator.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Generates illustrated graphic novel narratives about scientists, mathematicians, and historical figures for intelligent textbooks, with image prompts for each panel. Use when adding historical-figure or case-study stories to a textbook's Stories section.
Installs and configures intelligent-textbook infrastructure - scaffold a brand-new MkDocs Material textbook (init textbook), install any of 40 features (math, mascot, learning graph viewer, Google Analytics GA4, custom 404, kanban board), and generate book metrics. Routes to the appropriate installation guide.
Creates interactive educational MicroSims, routing to the best-matched generator - p5.js, Chart.js, Plotly, Mermaid, vis-network, timelines, maps, Venn, causal-loop/feedback-loop diagrams (CLD), concept-classifier sorting quizzes, infographic overlays with callout labels, and Docker Python labs (runnable code blocks). Generates complete MicroSim packages with HTML, JavaScript, CSS, documentation, and metadata.
Generates a comprehensive learning graph from a course description, including 200 concepts with dependencies, taxonomy categorization, and quality validation reports. Use this when the user wants to create a structured knowledge graph for educational content.
Wires Google Analytics 4 into an MkDocs Material site — creates a GA4 property, writes the Measurement ID into mkdocs.yml, verifies the tag, and deploys. Use when adding analytics to a textbook for the first time.
Generates detailed chapter content for an intelligent textbook — text, diagrams, MicroSims, and exercises at the appropriate Bloom's level. Use when a chapter's index.md exists with title, summary, and concept list.
| name | course-description-analyzer |
| description | Validates or creates a course description for an intelligent textbook, scoring completeness against required elements (title, audience, prerequisites, topics, Bloom's Taxonomy outcomes). Use before running the learning-graph-generator. |
| model | sonnet |
| license | Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) |
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.
Start by checking if /docs/course-description.md exists:
Tell the user that they are running Version 0.03 of the Course Description Analyzer Skill.
Use this workflow when /docs/course-description.md does not exist.
Ask the user the following questions sequentially (not all at once):
What is the title of the course?
What is the target audience of the course?
What are the prerequisites for this course?
What are the main subjects/topics covered by this course?
What are the learning outcomes organized by the 2001 Bloom's Taxonomy?
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:
After creating the file, automatically proceed to Step 2 (Analysis Workflow) to validate the newly created course description and provide a quality score.
Use this workflow when /docs/course-description.md already exists.
Read /docs/course-description.md and analyze its contents against the quality criteria.
Evaluate the course description using this 100-point scoring system:
| Element | Points | Criteria |
|---|---|---|
| Title | 5 | Clear, descriptive course title present |
| Target Audience | 5 | Specific audience identified (e.g., "college undergraduate") |
| Prerequisites | 5 | Prerequisites listed or explicitly stated as "None" |
| Main Topics Covered | 10 | Comprehensive list of topics (ideally 5-10 topics) |
| Topics Excluded | 5 | Clear boundaries set for what's NOT covered |
| Learning Outcomes Header | 5 | Clear statement: "After this course, students will be able to..." |
| Remember Level | 10 | Multiple specific outcomes for remembering/recalling |
| Understand Level | 10 | Multiple specific outcomes for understanding/explaining |
| Apply Level | 10 | Multiple specific outcomes for applying/using |
| Analyze Level | 10 | Multiple specific outcomes for analyzing/breaking down |
| Evaluate Level | 10 | Multiple specific outcomes for evaluating/judging |
| Create Level | 10 | Multiple specific outcomes for creating/synthesizing; includes capstone ideas |
| Descriptive Context | 5 | Additional context about course importance, relevance, or value |
Scoring Guidelines:
Identify missing or weak elements:
Provide specific, actionable recommendations:
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
Overall Score: X/100
Quality Rating:
Detailed Scoring Breakdown: Show points earned for each element
Gap Analysis: List of missing or weak elements
Improvement Suggestions: Prioritized recommendations
Next Steps:
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
---
Assess whether the course description contains sufficient detail to generate 200 concepts:
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
For all users with a score over 85, ask if the learning-graph-generator skill should be run next.
When using this skill:
course-description-template.md: Template structure for creating new course descriptions with all required sections and Bloom's Taxonomy framework