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.
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:
---