YouTube Summarizer
Download YouTube video transcripts/subtitles and generate structured content summaries with key viewpoints, notable quotes, and topic analysis.
Setup
Install dependencies (skip if already installed):
pip3 install youtube-transcript-api -q
# yt-dlp is needed for video metadata (title, channel, duration)
# Install if not present: brew install yt-dlp OR pip3 install yt-dlp
Workflow
Step 1: Fetch Transcript
SKILL_DIR is the directory containing this SKILL.md file.
# JSON output with metadata
python3 SKILL_DIR/scripts/fetch_transcript.py "https://youtube.com/watch?v=VIDEO_ID"
# Plain text with timestamps (recommended for summarization)
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --text-only --timestamps
# Specific language with fallback chain
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --language en,zh --text-only --timestamps
The script accepts any standard YouTube URL format: watch?v=, youtu.be/, shorts/, embed/, live/, or a raw 11-character video ID.
Step 2: Fetch Video Metadata
Get title, channel, duration, and upload date for context:
yt-dlp --skip-download --print "%(title)s|%(channel)s|%(duration_string)s|%(upload_date)s" "URL"
Step 3: Read Full Transcript
For long videos (>30 min), the transcript output may be large. Read in sections:
# First half
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --text-only --timestamps | head -500
# Second half
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --text-only --timestamps | tail -400
Step 4: Generate Summary
Analyze the transcript and produce a structured summary. ALL content must be in the chosen language — including section labels, table headers, and metadata fields. Only the template structure (emojis, table format, blockquote format) stays fixed. The actual words are all localized.
Template structure (translate every label into the output language):
## [localized: "视频总结" / "Video Summary"]
**[localized label]:** (title)
**[localized label]:** (channel)
**[localized label]:** (guest, if identifiable)
**[localized label]:** (duration) | **[localized label]:** (date)
---
### [localized: one-line summary]
(1-2 sentence overview)
---
### [localized: "核心观点" / "Key Viewpoints"]
| [localized: 话题] | [localized: 观点] |
|-------|-----------|
| ... | ... |
---
### [localized: "金句" / "Notable Quotes"]
> "Original language quote" — Speaker
---
### [localized: "其他亮点" / "Other Highlights"]
- ...
---
### [localized: "注意/偏见" / "Notes / Bias"]
- ...
Output Language
The summary language is determined by this priority:
- User explicitly specifies (e.g. "用中文总结", "summarize in Japanese", "用英语总结") → use that language
- User does not specify → default to 中文 (Chinese) for ALL content
- Quotes → always keep in the original spoken language (do not translate quotes)
- Section labels, table headers, metadata fields → translate into the output language (中文 by default)
- Only structural format (tables, blockquotes, bold) stays fixed — no emojis
Error Handling
| Error | Solution |
|---|---|
youtube-transcript-api not installed |
Run pip3 install youtube-transcript-api |
Transcripts are disabled |
Tell user subtitles are disabled for this video |
No transcript found |
Retry without --language flag, then note actual language |
| Empty output | Video may not have auto-generated subtitles; inform user |
yt-dlp: command not found |
Install with pip3 install yt-dlp or brew install yt-dlp |
Reference Example
See references/example-output.md for a real summary (GLM-5.2 interview video, Chinese output). Use it as the quality bar for structure, conciseness, and depth.
Tips
- Speaker identification: For interview/podcast videos, identify speakers from the intro and label viewpoints accordingly
- Sponsor segments: Skip ad reads (common in tech videos) — note them in ⚠️ section
- Long videos (>1hr): Process in chunks; the script outputs ~500-800 lines for a typical 1.5hr video
- Non-English videos: The transcript will be in the video's language; summarize in the output language per the rules above (default 中文)