learning-graph-generator

Generate a DAG-based concept network with dependency edges from a course description.

1|1|Updated Nov 22, 2025

Search Tags:#validation #dependencies #concepts #learning-graph #DAG

Ready to run

npx skills add https://github.com/vishalsachdev/database-management --skill learning-graph-generator-vishalsachdev

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: learning-graph-generator
Source: https://github.com/vishalsachdev/database-management/tree/main/.claude-skills/skills/learning-graph-generator
Command: npx skills add https://github.com/vishalsachdev/database-management --skill learning-graph-generator-vishalsachdev

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires jsonschema.

What problem does it solve?

This skill builds a complete learning graph (DAG) from a course description, enabling AI-assisted sequencing of concepts and validation of graph quality.

Core Features & Use Cases

DAG-based concept network: hundreds of concepts with dependencies.
Quality validation: provides reports for DAG validity, indegree/outdegree, cycles, and orphan nodes.
Vis-network export: supports CSV/JSON formats for visualization and editing.

Quick Start

Trigger the skill after the course description and concept list exist; use the provided scripts to validate, export, and inspect the graph.

Frequently Asked Questions about learning-graph-generator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate a learning graph from a course description?▼

A learning graph generator builds a DAG (directed acyclic graph) that maps concepts and their prerequisite dependencies from your course description. It produces structured outputs including taxonomy categorization, dependency edges, and quality validation reports to ensure the graph is acyclic and complete.

What validation does a learning graph perform on concept dependencies?▼

Learning graph validation checks for cycles, orphan nodes, and analyzes indegree/outdegree metrics to ensure the DAG is valid. It detects broken prerequisite chains and provides actionable reports to fix structural issues before exporting.

Can I export a learning graph as CSV or JSON for visualization?▼

Yes. The skill exports concept graphs in CSV and JSON formats compatible with visualization tools and Markdown documentation. Outputs include MkDocs-compatible Markdown, metadata, and formats suitable for editing and third-party rendering.

Who should use a learning graph for course design?▼

Course designers, educators, and AI textbook authors use learning graphs to sequence hundreds of concepts logically and validate prerequisite structures. It's essential for mapping complex curricula and ensuring dependencies don't create circular requirements.

What input does a learning graph generator need to start?▼

Provide a course description and a list of concepts. The skill processes these inputs using jsonschema validation to generate a complete DAG with taxonomy assignments, dependency edges, and quality metrics.

Why would a learning graph show orphan nodes or cycles?▼

Orphan nodes appear when concepts lack prerequisites or dependents; cycles occur when circular dependencies form. Identifying these structural issues through validation prevents invalid course sequences and helps designers refine concept relationships.