kakomon-subject-audit

To audit university subject PDFs, cross-check past exam PDFs with official PDFs to identify missing variants, answer omissions, and data quality issues. This process applies phase-based data quality checks to ensure accurate, deduplicated records.

Normalizing subject names during university past exam data reconciliation involves applying subject_variant gates and YAML frontmatter metadata. This ensures consistent data handling and resolves notation variations across multiple subject bundles.

Yes, you can add and modify university subjects that are not yet registered in the database. The workflow supports subject-level audits for universities with multiple variants, ensuring proper normalization and deduplication of newly added records.

The phase-based data quality check process works through structured phases from Phase 1 to Phase 5 with specific guard conditions. It handles science subject bundles by enforcing subject_variant gates to guide accurate, deduplicated record creation.

Yes, YAML frontmatter metadata containing name and description fields is required to perform a subject-level data audit. This metadata enforces structure and guides the phase-based checks to ensure accurate reconciliation of university subject records.

Duplicate records and notation inconsistencies appear when past exam PDFs and official PDFs are not properly reconciled. Applying subject_variant gates and normalizing subject names resolves these data quality issues during the audit workflow.