lecture-slides
Skill0 starsChanged 2 months agoMITView on GitHub
Build a Korean in-house lecture (딥러닝 강의 style) from the lecturer's drafts: a Slides artifact deck with speaker notes, a polished final script, an ElevenLabs phonetic script (소리 나는 대로 + break tags), and — when the lecture has a practice notebook — a renamed, cleaned .ipynb pushed to the course GitHub repo with a Colab badge and README row. Use when the user hands over "대본 초안", "PPT 초안", "슬라이드 초안" or an .ipynb for the next lecture ("N강을 만들려고 합니다", "슬라이드와 대본을 만들어 주세요", "최종 대본과 일레븐랩스 대본", "슬라이드를 이전 스타일과 유지되도록"), or asks to revise a lecture deck, sync notes with a reviewed script, or add figures/formula images to a lecture slide. The narrated video itself is the lecture-video skill's job.
4 other projects use a version of this.
Adopted by
Most recently taken up by
- methylo/claude-skill-booktheir own version, first seen Nov 8, 2026
- zi-yue-1129/research-lab-skillstheir own version, first seen Nov 8, 2026
- EtherealMingo/university-teacher-skillstheir own version, first seen Oct 20, 2026
- YuliangXiu/lecture-slidestheir own version, first seen Sep 20, 2026
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 4
- EtherealMingo/university-teacher-skills★ 16same name
- YuliangXiu/lecture-slides★ 12same name
- zi-yue-1129/research-lab-skills★ 9same name
- methylo/claude-skill-book★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository3 other files it gives its agents.
- arxiv-korean-translationSkill
- lecture-videoSkill
- obsidian-todo-syncSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 90
When the user's wording is technically wrong (e.g.
- Distinctive: line 93
Verify every quoted number against the notebook output.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Lecture Slides
Turns a lecturer's rough drafts into four deliverables that stay in sync:
| Deliverable | Where |
Slide deck (Slides artifact, one <aside> of notes per slide) | claude.ai artifact |
N강_최종대본.txt — final script, N페이지 + 코드 N sections | lecture folder |
N강_일레븐랩스_PPT.txt, N강_일레븐랩스_코드.txt — TTS scripts | lecture folder |
NN_topic/NN_topic.ipynb + README row | course GitHub repo |
The look, the slide recipes, the script rules and the notebook rules are in the reference files. Read the one you need before starting that step:
reference/style.md— palette, type scale, slide archetypes, layout budgetreference/slides-howto.md— artifact mechanics, diagrams, images, revisingreference/script.md— polishing the draft, final script format, ElevenLabs rulesreference/notebook.md— notebook conventions, local run, Colab check, GitHubtemplates/*.html— copy-ready slide files for each archetype
Workflow
- Read everything first. The script draft (
N강 대본 초안.txt), the PPT draft (export to PNG to look at it —reference/slides-howto.md), any images in the folder orbackup/, and the notebook. Drafts may be mojibake in the first half and clean UTF-8 later; find the readable copy. - Ask only what changes the work (one AskUserQuestion, ≤3 questions):
- notebook folder/file name (
NN_topic/NN_topic.ipynb, recommend one), - the user's own figures: redraw in deck style, or insert as images (if the user drew a figure carefully, inserting it is usually right — see "Lessons"),
- anything the draft leaves open (which experiments, who writes a missing script section). Everything else: decide, state the assumption in one line, go.
- notebook folder/file name (
- Notebook (if any) →
reference/notebook.md: rename, format like the previous lecture, fix wrong comments, run locally, push, README row. Get the numbers the script will quote from the run. - Deck →
reference/slides-howto.md+reference/style.md: one idea per slide, notes = the polished script for that page, citations for paper figures, a closing "코랩에서 직접 실행" slide with the notebook URL when there is a notebook. - Scripts →
reference/script.md: the review draft first (N강_대본.txtorN강_코드대본.txt) when the user wants to review; the final script and ElevenLabs files once they have reviewed. - Report: what changed, the numbers used and where they came from, and a short "확인해 주세요" list (factual fixes you made to their wording, pronunciations you guessed, anything not verified). Never claim a render or a Colab run you did not do.
Rules that came from the user
- Commit/push only when asked; the user asks explicitly ("올리고 확인", "깃허브에 올려줘"). Never delete their files; keep originals beside the renamed copy.
- Their edits win. The deck is edited in the browser and sometimes in a downloaded PPTX. Before touching a slide, read its current version from the artifact; change only what was asked; keep their widths, wording, images.
- Numbers follow Colab, because the video is recorded on Colab. If you only ran locally, say so and round ("약 0.29").
- The last code scene ends with the next-lecture line ("다음 시간에는 … 살펴보겠습니다."), then "감사합니다." Ask or leave a placeholder if the next topic is unknown.
- Korean throughout, polite 합니다체 in scripts; slides use short noun-phrase or 다/음 endings.
Lessons
- A redrawn diagram can lose what the user's figure showed (lecture 8: the residual-connection backprop flow). When the user supplies a careful figure, insert it (upload as asset) and put short takeaway cards beside it.
- Formula images the user pastes (PNG of LaTeX) go in a white card
(
background:#FFFFFF) at native size — scaling up blurs them. - When the user's wording is technically wrong (e.g. "squaring the gradient = second derivative", "Wide ↔ Deep inputs swapped"), fix it in the script and list it under "확인해 주세요"; do not silently keep or silently change.
- Verify every quoted number against the notebook output; compute any derived claim (e.g. "baseline loss equals predicting the mean") before saying it.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

