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WALKERKILLER
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Transcribe a single Tongji Look lecture video to SRT + TXT, optionally download slide snapshots in parallel.

Overview

PublisherWALKERKILLER
RepositoryLook-Tongji-Notes
Skill nametrans
Stars
51
Forks
7
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by WALKERKILLER on GitHub. Read the source before you install it.

Installation

Install the Trans AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/WALKERKILLER/Look-Tongji-Notes/tree/main/skills/trans
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/WALKERKILLER/Look-Tongji-Notes.git /tmp/Look-Tongji-Notes
mkdir -p .claude/skills
cp -r /tmp/Look-Tongji-Notes/skills/trans .claude/skills/trans
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Trans in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Trans on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Trans is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Transcribe

Transcribe one lecture video from look.tongji.edu.cn and optionally download slide snapshots.

When to Use

  • User says /trans or "transcribe this lecture".
  • User provides a lecture URL or course_id + sub_id.

Workflow

  1. Resolve lecture with URL or IDs:
bash
python "<SKILL_DIR>/../../scripts/look_tongji.py" transcribe --lecture-url "<LECTURE_URL>"
bash
python "<SKILL_DIR>/../../scripts/look_tongji.py" transcribe --course-id "<ID>" --sub-id "<ID>"
  1. Transcribe + download slides in one run:
bash
python "<SKILL_DIR>/../../scripts/look_tongji.py" transcribe --course-id "<ID>" --sub-id "<ID>" --slide
  1. The CLI prints real-time progress. Stdout contains result paths.

Non-Interactive / Batch Usage

When running from an automated pipeline, avoid input() prompts with these flags:

FlagDescription
--sub-idSpecify lecture sub_id directly (skips interactive lecture picker)
--course-idSpecify course ID directly (skips interactive course selection)
--slideDownload slides after transcription
--concurrency NSlide download concurrency (default 4)
--retries NSlide download retries (default 3)

manifest.json — Required for Wiki Build

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:

json
{
  "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:

  • Use absolute paths for all artifact paths (relative paths break on Windows)
  • duration_seconds: must be ≥ 3600 (1 hour); if < 3600, the lecture is marked不合格 and wiki shows it as 缺失
  • If no slides were downloaded, leave slides field empty ("")
  • Fields notes and timeline are filled by /note command later

Artifacts

  • <course_id>_<sub_id>.srt — subtitle with timestamps
  • <course_id>_<sub_id>.txt — plain text transcript
  • <course_id>_<sub_id>.json — metadata
  • slides/ — slide images + index.json (if --slide)
  • manifest.json — MUST create manually after transcription

One Session Per Call

For batch transcribing, use /ralphtrans.

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/`).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Trans AI skill do?

Transcribe a single Tongji Look lecture video to SRT + TXT, optionally download slide snapshots in parallel.

Why use Trans on TypingMind?

Because you install it once and use it with any model. Trans is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Trans in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/WALKERKILLER/Look-Tongji-Notes/tree/main/skills/trans. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Trans?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Trans?

As many as you like. As long as a model supports skills, you can use Trans with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Trans AI skill free?

Yes. It is published on GitHub by WALKERKILLER under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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