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trans
Transcribe a single Tongji Look lecture video to SRT + TXT, optionally download slide snapshots in parallel.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Transcribe a single Tongji Look lecture video to SRT + TXT, optionally download slide snapshots in parallel.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
9-command agent skill suite for Tongji Look (look.tongji.edu.cn): setup, list, transcribe, take notes, manage materials, build course wiki, create cheat sheets, batch-process entire courses, and deploy course wiki to GitHub Pages.
Add supplementary materials (PDF, PPTX, DOCX, images) to a lecture session. Converts to Markdown via MarkItDown and indexes into the course wiki — without triggering transcription or slide download.
Generate a high-density A4 cheat sheet for open-book exams. Two output paths: LaTeX (XeLaTeX) or self-contained HTML with CSS print layout. Both paths produce visually consistent results.
Discover and select courses from Tongji Look (look.tongji.edu.cn). Lists recent or all courses, filters by keyword, and saves the chosen course for use with /trans, /note, and other commands. Prerequisite for all lecture workflows.
Generate study notes from a lecture transcript and slides. Runs transcript + slide download in parallel, then writes a Markdown note with timeline outline.
Deploy the built course wiki site/ to GitHub Pages via gh CLI. Pre-checks gh auth status and site/ existence.
| name | trans |
| description | Transcribe a single Tongji Look lecture video to SRT + TXT, optionally download slide snapshots in parallel. |
| license | MIT |
| metadata | {"author":"WALKERKILLER","version":"1.1"} |
Transcribe one lecture video from look.tongji.edu.cn and optionally download slide snapshots.
/trans or "transcribe this lecture".python "<SKILL_DIR>/../../scripts/look_tongji.py" transcribe --lecture-url "<LECTURE_URL>"
python "<SKILL_DIR>/../../scripts/look_tongji.py" transcribe --course-id "<ID>" --sub-id "<ID>"
python "<SKILL_DIR>/../../scripts/look_tongji.py" transcribe --course-id "<ID>" --sub-id "<ID>" --slide
When running from an automated pipeline, avoid input() prompts with these flags:
| Flag | Description |
|---|---|
--sub-id | Specify lecture sub_id directly (skips interactive lecture picker) |
--course-id | Specify course ID directly (skips interactive course selection) |
--slide | Download slides after transcription |
--concurrency N | Slide download concurrency (default 4) |
--retries N | Slide download retries (default 3) |
transcribe does NOT automatically create manifest.json. After transcription, you MUST create it manually so the wiki indexer can find this lecture.
Create manifest.json in the session's 原始数据/ directory with this structure:
{
"course_id": "COURSE_ID",
"sub_id": "SUB_ID",
"course_title": "课程名称(真实中文名)",
"session_title": "YYYY-M-D 第X节",
"base_name": "COURSE_ID_SUB_ID",
"artifacts": {
"srt": "F:\\workspace\\raw\\课程名称\\YYYY-M-D 第X节\\原始数据\\COURSE_ID_SUB_ID.srt",
"txt": "F:\\workspace\\raw\\课程名称\\...\\COURSE_ID_SUB_ID.txt",
"notes": "",
"timeline": "",
"slides": "F:\\workspace\\raw\\课程名称\\...\\slides\\index.json"
},
"duration_seconds": 5580
}
Critical path rules:
duration_seconds: must be ≥ 3600 (1 hour); if < 3600, the lecture is marked不合格 and wiki shows it as 缺失slides field empty ("")notes and timeline are filled by /note command later<course_id>_<sub_id>.srt — subtitle with timestamps<course_id>_<sub_id>.txt — plain text transcript<course_id>_<sub_id>.json — metadataslides/ — slide images + index.json (if --slide)manifest.json — MUST create manually after transcriptionFor batch transcribing, use /ralphtrans.
`<SKILL_DIR>` is the directory containing this `SKILL.md`. Shared scripts (`look_tongji.py`, `timeline_tools.py`, `tongji_backend/`) and references live two levels up in the repository root (`<SKILL_DIR>/../../scripts/` and `<SKILL_DIR>/../../references/`).