faq-generator

To generate Bloom's Taxonomy-aligned FAQs from textbook content, provide the course description, learning graph, glossary, and at least 30% of chapter content. The system outputs structured questions across six categories to docs/faq.md and chatbot training JSON files.

Creating chatbot-ready FAQ training data involves structuring course content into categorized question-and-answer pairs. This skill exports Bloom's-aligned outputs directly to docs/learning-graph/faq-chatbot-training.json for RAG integration in educational apps.

Yes, you can use a learning graph and glossary to automate FAQ generation. Supplying these alongside course descriptions and chapter content produces structured, self-guided learning FAQs mapped across Bloom's levels for chatbot readiness.

Required inputs for producing a structured FAQ set for RAG integration include a course description, learning graph, glossary, and a minimum of 30% chapter content. These elements ensure accurate generation of categorized Bloom's-aligned questions and quality reports.

Yes, the generated FAQ output includes six standard categories: Getting Started, Core Concepts, Technical Details, Common Challenges, Best Practices, and Advanced Topics. This category-driven structure supports self-guided learning and chatbot readiness.