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

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.