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Course Description Analyzer

  • 6 installs
  • 2 repo stars
  • Updated August 1, 2026
  • vishalsachdev/claude-skills

Helps with ai & agent building tasks.

About

course-description-analyzer is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • course-description-analyzer
  • AI & Agent Building
  • AI-coding skill

Course Description Analyzer by the numbers

  • 6 all-time installs (skills.sh)
  • +1 installs in the week ending Jul 27, 2026 (Skillselion tracking)
  • Ranked #12,739 of 16,556 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 2, 2026 (Skillselion catalog sync)
npx skills add https://github.com/vishalsachdev/claude-skills --skill course-description-analyzer

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Listed on Skillselion
Installs6
repo stars2
Last updatedAugust 1, 2026
Repositoryvishalsachdev/claude-skills

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

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

3. What are the prerequisites for this course?

  • If none, explicitly state "None"

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

  • Request a list of major topics

5. 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

3. Detailed Scoring Breakdown: Show points earned for each element 4. Gap Analysis: List of missing or weak elements 5. Improvement Suggestions: Prioritized recommendations 6. 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

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