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Automation
Skill

/find-yonsei-attendance-discrepancies

Compare displayed and user-expected statuses from the authorized live Yonsei attendance page first, identify records explicitly disputed by the user, and report which items have enough reason and evidence to draft a correction; use a screenshot, pasted table, export, or JSON

From plugin
yonsei-skills
952 skills1 MCP
Install
$ npx -y skills add mrcha033/yonsei-skills --skill find-yonsei-attendance-discrepancies --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/find-yonsei-attendance-discrepancies

Context preview

The summary Claude sees to decide when to auto-load this skill.

Compare displayed and user-expected statuses from the authorized live Yonsei attendance page first, identify records explicitly disputed by the user, and report which items have enough reason and evidence to draft a correction; use a screenshot, pasted table, export, or JSON

SKILL.md

find-yonsei-attendance-discrepancies.SKILL.md
name: find-yonsei-attendance-discrepancies
description: Compare displayed and user-expected statuses from the authorized live Yonsei attendance page first, identify records explicitly disputed by the user, and report which items have enough reason and evidence to draft a correction; use a screenshot, pasted table, export, or JSON only when the live page is unavailable or intentionally supplied. Use without inferring presence or changing official records.

Find Yonsei Attendance Discrepancies

Return one discrepancy report from a supplied review snapshot.

Prepare the input

If the user supplies an attendance screen or table, extract the displayed records into a private temporary JSON file, then ask the user which entries they dispute and what evidence they want considered. Do not make the user write JSON or infer an expected status from location or timetable data.

Run

python3 "$SKILL_DIR/scripts/find_discrepancies.py" --input attendance-review.json

Each record needs course, date, and `recorded_status`. Supply `expected_status` when known, or set `user_disputed: true`. Set `reviewed: true` for a record the user checked and accepts. A discrepancy is ready for a draft only when it has a different expected status, a reason, and at least one evidence description.

`no_discrepancies_found` is true only when every row is explicitly reviewed. Unreviewed rows remain `unknowns`.

Boundaries

  • Never infer presence from timetable, location, Bluetooth, device, or network data.
  • Process only user-supplied attachments, pasted data, or JSON and reject credential, session, check-in, beacon, or location fields.
  • Do not accuse a person or system of error; report a user-review candidate.
  • Never submit a correction or alter an attendance record.
Read more
Ships withyonsei-skills

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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