Youtube Interview Shorts Zh

Overview

Use this skill to convert one long YouTube interview into multiple short Chinese-subbed clips that are ready to review or post. It bundles the download, transcript parsing, clip cutting, subtitle windowing, and subtitle/title burn-in helpers.

When To Use

• The user gives a YouTube interview, talk, keynote, or podcast URL and wants multiple short clips.
• The user wants Chinese hard subtitles burned into each final clip.
• The user wants review-friendly candidate clip suggestions before export, or explicitly wants you to pick the best set yourself.

Workflow

1. Confirm prerequisites.
   Check yt-dlp and ffmpeg availability first. The helper scripts can use system ffmpeg or the imageio-ffmpeg binary fallback.

2. Create a work layout.
   Use a layout like:

work/<video-slug>/
  source/
  analysis/
  clips/

3. Download source assets.
   Run download_youtube.py with the YouTube URL and the source/ directory. This downloader prefers browser cookies, falls back from English subtitles to zh-Hans, and uses the more reliable Android client path for the MP4 download.

4. Inspect the downloaded files.
   Identify:

• the source .mp4
• the subtitle .srt
• any sidecar files such as .ytdl

5. Parse the subtitle file into JSON.
   Use srt_to_json.py and save the artifact into analysis/transcript.json.

6. Analyze before cutting.
   Read clip-schema.md and analysis-prompt.md. Generate a generous candidate list, then write analysis/selected_clips.json and analysis/candidate-review.txt.

7. Candidate rules.

• Target 5 to 8 exported clips unless the user asks for another count.
• Prefer clips between 20 and 180 seconds.
• Favor one clear idea per clip.
• Favor strong opening lines, complete endings, and minimal dependency on missing context.
• Reject filler, greetings, sponsor reads, and fragments that end mid-thought.

8. Export each chosen clip.

• Cut the video with clip_video.py
• Window the subtitle file with window_srt.py
• If the source subtitle is English, translate the local clip SRT into simplified Chinese while preserving timestamps as closely as possible
• If the source subtitle is already Chinese, keep it and lightly clean only obvious duplication or noise
• Burn subtitles and a first-second title with burn_subtitles.py

9. Packaging copy.
   For each exported clip, create:

• one short, sharp Chinese title
• one Chinese description under 140 characters

Write per-clip metadata into each clip folder and also compile a combined analysis/clip-packaging.txt.

File Layout

Use:

work/<video-slug>/
  source/
    original.mp4
    original.<lang>.srt
  analysis/
    transcript.json
    selected_clips.json
    candidate-review.txt
    clip-packaging.txt
  clips/
    01-<slug>/
      clip.mp4
      clip.zh.srt
      clip.hardsub.mp4
      metadata.txt

Script Notes

• Run the helper scripts from the skill root with PYTHONPATH="$PWD" when using python3 -m scripts.<name>.
• Prefer PingFang or another local Chinese font when burning titles and subtitles. If no better font is available, let the script fall back to the system default.
• The downloader uses Chrome cookies when available. If download fails because cookies are stale, refresh browser login state before changing the workflow.

Resources

• Scripts:
  download_youtube.py,
  srt_to_json.py,
  window_srt.py,
  clip_video.py,
  burn_subtitles.py
• References:
  clip-schema.md,
  analysis-prompt.md

Output Contract

Return:

• the source asset folder
• the candidate clip list with timestamps, duration, title, and two-sentence summaries
• the packaging text file path
• the final clip.hardsub.mp4 path for each exported short

If the workflow cannot finish, report the exact blocker, such as stale cookies, failed download, missing subtitles, missing ffmpeg, or unusable transcript quality.