kakomon-subject-audit

Audit university subject data by cross-checking past exam PDFs with official PDFs.

Updated Aug 27, 2026

Search Tags:#pdf #audit #normalization #data-quality #university #kakomon #subject-variant

Ready to run

npx skills add https://github.com/stsrjkt-bit/claude-plugins --skill kakomon-subject-audit

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: kakomon-subject-audit
Source: https://github.com/stsrjkt-bit/claude-plugins/tree/main/kakomon-subject-audit/skills/kakomon-subject-audit
Command: npx skills add https://github.com/stsrjkt-bit/claude-plugins --skill kakomon-subject-audit

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

特定の大学×科目について、DBの過去問PDFと公式サイトの公開PDFを突合し、不足（バリアント漏れ・解答欠落）や不正データ（重複・誤レコード）を発見・修正するワークフロー。対象科目がDB未登録の場合でも追加・修正を支援し、表記揺れの正規化やバリアントの整合性を確保します。

Core Features & Use Cases

対象科目の差分監査: ingested 大学データに対して、過去問PDFと公式PDFを突合して差分を洗い出す。
データ品質の改善: 重複・解答欠落・表記揺れなどの不整合を検出・修正して信頼性を高める。
運用ワークフローの自動化: Phase 1〜Phase 5 の段階的手順とガード条件を整理し、再現性のある監査を実現する。

Quick Start

対象大学×科目の監査を開始して、差分検出とデータ品質改善を実行してください。

Frequently Asked Questions about kakomon-subject-audit

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

FAQPage Schema

How do I audit university subject PDFs to find missing exam variants and answer omissions?▼

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.

What is the best way to normalize subject names when reconciling university past exam data?▼

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.

Can I use this workflow to add university subjects that are not yet registered in the database?▼

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.

How does the phase-based data quality check process work for science subject bundles?▼

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.

Do I need YAML frontmatter metadata to perform a subject-level data audit?▼

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.

Why are duplicate records and notation inconsistencies appearing in my university subject database?▼

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.