Download videos from any platform and generate a complete resource package including:
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionvideo-summarizerExecute the skills CLI command in your project's root directory to begin installation:
Fetches video-summarizer from liang121/video-summarizer and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate video-summarizer. Access via /video-summarizer in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Download videos from any platform and generate a complete resource package including:
Supports all 1800+ websites supported by yt-dlp.
When the user:
All files are saved to downloads/<video-title>/ in the current working directory:
./downloads/
└── <video-title>/
├── video.mp4 # Original video
├── audio.mp3 # Extracted audio
├── subtitle.vtt # Subtitles with timestamps
├── transcript.txt # Plain text transcript (no timestamps)
└── summary.md # Structured summary
Run the install script to check and install all dependencies:
bash "$SKILL_DIR/scripts/install_deps.sh"
This installs: uv (Python package manager), ffmpeg, yt-dlp, and checks Python version. faster-whisper will be automatically managed by uv.
# Get video title (sanitize special characters for folder name)
TITLE=$(yt-dlp --print "%(title)s" "VIDEO_URL" | sed 's/[/:*?"<>|]/_/g' | cut -c1-80)
DURATION=$(yt-dlp --print "%(duration)s" "VIDEO_URL")
# Create output directory
OUTPUT_DIR=./downloads/"$TITLE"
mkdir -p "$OUTPUT_DIR"
# Download video (mp4 format, best quality up to 1080p)
yt-dlp -f "bestvideo[height<=1080][ext=mp4]+bestaudio[ext=m4a]/best[height<=1080][ext=mp4]/best" \
--merge-output-format mp4 \
-o "$OUTPUT_DIR/video.%(ext)s" "VIDEO_URL"
# Extract audio (mp3 format)
yt-dlp -x --audio-format mp3 -o "$OUTPUT_DIR/audio.%(ext)s" "VIDEO_URL"
Priority order:
yt-dlp --write-subs --sub-lang zh,en,zh-Hans,zh-Hant --skip-download \
-o "$OUTPUT_DIR/subtitle" "VIDEO_URL"
yt-dlp --write-auto-subs --sub-lang zh,en --skip-download \
-o "$OUTPUT_DIR/subtitle" "VIDEO_URL"
uv run "$SKILL_DIR/scripts/parallel_transcribe.py" \
--input "$OUTPUT_DIR/audio.mp3" \
--output-dir "$OUTPUT_DIR" \
--model small \
--language auto
The script automatically:
subtitle.vtt and transcript.txtTranscription Options:
| Option | Default | Description |
|---|---|---|
--model |
small | tiny/base/small/medium/large-v3 |
--language |
auto | Language code or 'auto' |
--workers |
CPU/2 | Number of parallel workers |
--min-segment |
60 | Min duration (sec) to enable splitting |
If subtitles were downloaded (not transcribed), convert to plain text:
if [[ ! -f "$OUTPUT_DIR/transcript.txt" ]]; then
SUBTITLE_FILE=$(ls "$OUTPUT_DIR"/*.vtt "$OUTPUT_DIR"/*.srt 2>/dev/null | head -1)
if [[ "$SUBTITLE_FILE" == *.vtt ]]; then
sed '/^[0-9]/d; /^$/d; /-->/d; /^WEBVTT/d; /^Kind:/d; /^Language:/d; /^NOTE/d' \
"$SUBTITLE_FILE" > "$OUTPUT_DIR/transcript.txt"
elif [[ "$SUBTITLE_FILE" == *.srt ]]; then
sed '/^[0-9]/d; /^$/d; /-->/d' "$SUBTITLE_FILE" > "$OUTPUT_DIR/transcript.txt"
fi
fi
$SKILL_DIR/reference/summary-prompt.md{{TITLE}}, {{PLATFORM}}, {{URL}}, {{DURATION}}, {{LANGUAGE}}, {{DOWNLOAD_TIME}}, {{TRANSCRIPT}}$OUTPUT_DIR/summary.md# Prioritize Chinese subtitles
yt-dlp --sub-lang zh-Hans,zh-Hant,zh ...
# If login required
yt-dlp --cookies-from-browser chrome "VIDEO_URL"
yt-dlp --cookies-from-browser chrome "VIDEO_URL"
# or firefox
yt-dlp --cookies-from-browser firefox "VIDEO_URL"
Use the parallel transcription script (Step 4, option 3).
yt-dlp --list-extractors | grep -i "platform-name"
./downloads/ in current working directoryPrerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
affaan-m/everything-claude-code
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Keeps context tight: video-summarizer is the kind of skill you can hand to a new teammate without a long onboarding doc.
Useful defaults in video-summarizer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added video-summarizer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend video-summarizer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: video-summarizer is focused, and the summary matches what you get after install.
video-summarizer has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added video-summarizer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in video-summarizer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
video-summarizer is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
video-summarizer has been reliable in day-to-day use. Documentation quality is above average for community skills.
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