Integer explanations end with the answer but phrasing varies enough
that regex extraction would mis-key questions. A wrong key is worse
than no question. NUM stays hand-added until NTA keys transcribed.
scripts/import_examgoal.py pulls the MIT-licensed examgoal-derived
14,973-question pickle and keeps the 9,813 fully-text MCQs with single
correct answers (2002-2025, all subjects). chapterGroup becomes our
chapter, chapter slug becomes our subtopic. Idempotent: skips stems
already present.
views.rs gains rich() — a read-side sanitizer matching the importer's
allowlist — and all six stem/option/solution render sites use it.
KaTeX auto-render (trust:false) added to head() for $$..$$ math.
db.rs gains nine CREATE INDEX statements; the chapter loader query
drops from ~5s to 6ms on the 9.8k-question bank. DATA.md rewritten
around the real pipeline with attribution.
scripts/expand_seed.py generates synthetic questions across the full JEE Main
syllabus taxonomy (15 chapters, 45 subtopics, correct MCQ/NUM split). Stems
are deliberately sparse so no-one mistakes them for NTA content.
DATA.md documents why there is no real scraper: NTA PDFs render questions as
images; pdftotext extracts only IDs. Every aggregator with structured data
built it through manual entry pipelines. The document lists realistic paths
to a real bank and the SQL schema for loading one.
