| name | bilibili-render-pdf |
| description | Use when the user provides a Bilibili URL (BV number) and wants LaTeX course notes rendered as PDF. Triggers: Bilibili link, BV号, 'B站视频笔记', '整理B站课'. Falls back to Whisper when no CC subtitles. |
Bilibili Render PDF
Turn a Bilibili video into a complete, compileable .tex note and a rendered PDF.
This skill extends the youtube-render-pdf workflow with Bilibili-specific adaptations.
Shared Rules
Read ../video-render-common/writing-and-figures.md for all writing rules, teaching content rules, figure handling, figure time provenance, and visualization guidelines. These rules are mandatory.
Bilibili vs YouTube: Key Differences
| Aspect | Handling |
|---|
| Subtitle scarcity | CC subtitles → Whisper speech-to-text → visual-only mode |
| Login-gated HD | 1080P+ requires cookies; use yt-dlp --cookies-from-browser chrome |
| Multi-part videos | Detect 分P videos, ask user which parts to process |
| URL formats | bilibili.com/video/BVxxxxxxx and b23.tv short links |
| Danmaku | Do not use danmaku as teaching content (too noisy) |
Goal
Same as youtube-render-pdf — produce a professional Chinese lecture note with cover image, key frames, and synthesis section.
Source Acquisition
Supplementary Material Discovery
Same as youtube-render-pdf — search for official slides AND official lecture notes before downloading video.
Additional Bilibili-specific notes:
- Many Chinese courses host slides on their own course websites or Gitee/GitHub repos
- Some courses have companion textbooks or reading lists — check the video description
- Google Slides/Docs strategy: try
/export/pdf URL pattern; fall back to video frames if export fails
- If slides are found, use slide screenshots as the primary figure source and ensure they appear in the final PDF rather than relying on video frames alone
- Official lecture notes are especially valuable for Bilibili courses where subtitles may be auto-generated and formula accuracy is lower
Metadata Inspection
- Inspect video metadata first (title, chapters, duration, thumbnail, subtitle availability)
- Detect multi-part (分P) videos — list all parts and ask user which to process
Subtitle Acquisition (Three-Level Fallback)
Priority 1: CC subtitles
yt-dlp --write-subs --sub-langs "zh-Hans,zh-CN,zh,ai-zh" --convert-subs srt \
--skip-download -o "%(title)s.%(ext)s" "<URL>"
Priority 2: Whisper speech-to-text
yt-dlp -x --audio-format wav -o "audio.%(ext)s" "<URL>"
tools/scripts/transcribe_faster_whisper.py audio.wav \
--out-prefix transcript.zh \
--model large-v3 \
--device cuda \
--compute-type float16 \
--language zh
Priority 3: Visual-only mode — skip subtitles, rely on dense frame sampling.
Video and Cover Download
- Download original cover image (highest-res thumbnail)
- Probe formats, choose highest downloadable resolution (1080P+ needs cookies)
- Keep all artifacts local
Delivery
- the final
.tex file
- the downloaded cover image
- any extracted or generated figure assets
- the compiled PDF
- the Whisper-generated SRT subtitle file, if speech-to-text was used
- evidence that the compiled PDF was visually inspected via rendered pages/contact sheet and corrected if needed
Rules
- Follow
ai-course-notes/CLAUDE.md conventions for LaTeX structure, boxes, and figures
- Always compile PDF twice (
xelatex two passes) to resolve references
- After the final compile, follow the PDF Visual QA workflow in
../video-render-common/writing-and-figures.md; do not mark the note complete until rendered pages have been inspected and layout/rendering issues fixed
- Prefer CC subtitles; fall back to Whisper only when unavailable
- For long videos, use the faster-whisper CUDA helper from the shared rules; do not silently run multi-hour CPU transcription
- For fixed-camera interviews with no slides/demos/whiteboard, use the cover only and do not repeat speaker-head frames in the body; generate concept diagrams/tables instead
- Skip non-teaching content (intros, sponsor segments, 一键三连, 关注投币)
- Use
[H] float placement for all figures
- Set
\noteauthors to "基于公开课程资料整理" or "基于 [Speaker Name] 授课内容整理" — never "XX & Codex" or similar
- Set
\notedate to the video's publish date or course semester — never \today
- Always fill
\videourl with the URL the user provided
- Keep
\repourl{https://github.com/hqhq1025/ai-course-notes} unchanged from the template default
- Do NOT use TikZ for any visualization — it causes compilation timeouts. Use tables or pre-generated images instead
Asset
assets/notes-template.tex: default LaTeX template to copy and fill
