dmccreary/claude-skills/course-description-analyzer

Claude Code and agent skill by dmccreary/claude-skills

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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.

Install

npx vskill@latest install dmccreary/claude-skills/course-description-analyzer

SKILL.md

Course Description Analyzer

Version: 0.05

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 0.05 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?
  1. 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:

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

After the course-description.md file has been added to the /docs directory, 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.

yml
nav:
- Home: index.md
- About: about.md
- Course Description: course-description.md
# ...other existing entries stay where they are...
- Learning Graph:
- Course Description Assessment: learning-graph/course-description-assessment.md

Every entry in nav is a YAML list item, so each one must begin with - , including the entries nested under a section such as Learning Graph. Keep the indentation the file already uses. A nested entry written without the dash makes mkdocs build --strict fail with "Expected nav to be a list".

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

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
55
Repository forks
6
7-day trend score
20

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 17 Mar 2026, 7 months ago.

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