Setup
Transcribing Lessons from Tongji Look Platform to Notes with Agent Skill.
npx -y skills add WALKERKILLER/Look-Tongji-Notes --skill setupAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
Copied from the file, not written here
Configure Tongji Look credentials, check system dependencies (Python, Node.js, ffmpeg, vision-support, XeLaTeX), and set up the persistent course-wiki workspace.
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
1.9 KB, as published. Nobody here has run it
Setup
Configure credentials, dependencies, and workspace for Look Tongji Notes.
When to Use
- User says
/setupor asks to configure the skill. - First-time setup before transcribing lectures.
- User wants to change or migrate the course knowledge-base path.
Workflow
- Run setup:
python "<SKILL_DIR>/../../scripts/look_tongji.py" setup
- Non-interactive workspace options:
python "<SKILL_DIR>/../../scripts/look_tongji.py" setup \
--workspace-root "<COURSE_WIKI_ROOT>" \
--owner-name "<OWNER_NAME>" \
--site-name "<OWNER_NAME>的课程知识库"
-
The CLI checks: Python deps (requests, playwright, python-dotenv, markdown, markitdown), ffmpeg, Node.js, vision-support config, and optionally XeLaTeX.
-
Vision Support setup: If
vision-support/config.jsondoes not exist, the CLI prints the init command. The embedded vision-support is at<SKILL_DIR>/../../vision-support/. Help the user configure a vision provider (OpenAI, Google, Anthropic, deepseek, dashscope, zhipuai, ollama, or custom). -
Verify vision-support: After configuration, test with:
node "<SKILL_DIR>/../../vision-support/scripts/vision.mjs" "<SKILL_DIR>/../../komari.jpg"The agent should correctly identify image content (should mention "red-haired girl" or equivalent).
-
Never ask for passwords in chat. Use interactive terminal input or environment variables.
Where <SKILL_DIR> Points
<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/).