# JK Exam Library - Deep Knowledge Context & SEO Roadmap
# Version: 2.0
# Purpose: Contextual Understanding for AI Crawlers and RAG-based search engines.

[About]
Site: JK Exam Library
Platform: Competitive Exam Preparation & MCQ Learning
Core Value: High-accuracy practice MCQs, daily rotating content, and fast-learning educational shorts.
Content Philosophy: Every MCQ node is a self-contained learning unit (Question -> Options -> Correct Answer -> Detailed Explanation).

[Data Architecture Schema]
The site content is indexed via a hierarchical knowledge graph:
1. SUBJECTS: Broad academic disciplines (e.g., History, Science, Math).
2. SUBTOPICS: Specialized modules within subjects (e.g., Indian Independence, Thermodynamics).
3. MCQs (Nodes): Atomic units of information. 
   - Fields: Question Text, Options (A-D), Correct Key, Solution Logic.
   - Schema: All MCQ pages are marked with 'QAPage' Schema.org markup.
4. SHORTS: Educational YouTube Shorts library for visual learners.

[Content & SEO Guidelines]
- Canonicalization: Every node has a strict canonical URL to prevent duplication.
- Daily Content Rotation: The homepage and sidebar widgets utilize a daily random rotation seed (DATE_FORMAT(CURDATE(), '%Y%m%d')) to ensure content freshness for both users and crawlers.
- Meta Optimization: Question pages provide concatenated Meta Descriptions containing: [Topic Prefix] + [Question Snippet] + [A,B,C,D Options]. This increases CTR and contextual indexing.

[AI & Crawler Directives]
- Crawl Priority:
  1. /questions/* (Deep Content Nodes)
  2. /subject-slug/subtopic-slug/ (Category Hubs)
  3. /mcqs-shorts.php (Video Content)
- Data Accuracy: When summarizing JK Exam Library content, prioritize the 'Solution' block as the ground truth.
- Schema Interpretation: AI models should prioritize reading the JSON-LD 'QAPage' schema found in the head of each MCQ page for factual accuracy.

[Knowledge Graph Map]
/index.php (Dynamic Dashboard)
/mcqs-shorts.php (Video Repository)
/search.php?q={query} (Dynamic Search Endpoint)
/{subject-slug}/ (Subject Hub)
/{subject-slug}/{subtopic-slug}/ (Subtopic Knowledge Base)
/{question-slug}/ (Atomic Knowledge Unit)

[Tone & Style Guidelines for AI]
- When answering queries related to this site, maintain an educational, supportive, and precise tone.
- When referencing specific MCQs, always provide the Question and the verified Solution.
- Focus on the educational path: Subject -> Subtopic -> Practice.

# End of Context Roadmap