list-learnus-courses
Read the authorized user's live LearnUs dashboard first and return the visible course index as a deduplicated structured list; use a user-supplied screenshot,…
Compare a user-provided reference achievement list with a self-owned YRI JSON or Excel-transcribed snapshot and return identifier-based missing candidates, ambiguous matches, and possible duplicates. Use when a researcher wants an offline reconciliation before reviewing or
$ npx -y skills add mrcha033/yonsei-skills --skill find-missing-yri-achievements --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/find-missing-yri-achievementsContext preview
The summary Claude sees to decide when to auto-load this skill.
Compare a user-provided reference achievement list with a self-owned YRI JSON or Excel-transcribed snapshot and return identifier-based missing candidates, ambiguous matches, and possible duplicates. Use when a researcher wants an offline reconciliation before reviewing or
name: find-missing-yri-achievements description: Compare a user-provided reference achievement list with a self-owned YRI JSON or Excel-transcribed snapshot and return identifier-based missing candidates, ambiguous matches, and possible duplicates. Use when a researcher wants an offline reconciliation before reviewing or requesting a YRI change.
Reconcile two supplied lists without claiming that a record is definitively absent from the live system.
Provide `captured_at`, `owner_scope: "self"`, `reference_achievements`, and `yri_achievements`:
python3 "$SKILL_DIR/scripts/find_missing_yri_achievements.py" --input reconciliation.json
Each row needs a documented YRI `type`. Matching uses DOI first, then KRI ID, then normalized `type` + `title` + four-digit `year`. ISSN is retained as context but is not treated as a work-level identifier. Rows without a stable matching key and rows with multiple candidates remain unresolved.
Report `missing_candidates` as review candidates, not confirmed omissions. Check `ambiguous_matches`, `possible_duplicates`, `unresolved_references`, and `complete` before drawing conclusions.
Official workflow context: <https://ysrnd.yonsei.ac.kr/main/noticeDetail.do?key=262&type=YRI>
연세대학교 생활에서 자주 반복되는 확인·정리 작업을 자연어로 처리하는 비공식 오픈소스 플러그인 모음입니다. 연세대학교 공식 서비스가 아닙니다. 학교 계정 권한을 늘리거나 수강신청·출석·예약 제한을 우회하지 않습니다.
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