video-summarizer

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Structure

• Ships 2 executable scriptsscripts/install_deps.sh, scripts/parallel_transcribe.py. Review what they do before enabling the skill for agents with tool access.
• No license declaredConfirm you may reuse this skill before importing it into your repository.
• The source hub's security checks flagged this skillGen Agent Trust Hub: fail (This skill automates video downloads and summarization but requires elevated system permissions (sudo) to install its dependencies. It executes remote installation scripts and accesses sensitive browser data, such as cookies, to bypass video platform restrictions. Furthermore, it processes video transcripts that may contain malicious instructions for the AI.); Snyk: warn (Risk: MEDIUM · 2 issues)

SKILL.md

---
name: video-summarizer
description: "Download videos from 1800+ platforms (YouTube, Bilibili, Twitter/X, TikTok, Vimeo, Instagram, etc.) and generate complete resource package with video, audio, subtitles, and AI summary. Actions: summarize, download, transcribe, extract video content. Platforms: youtube.com, bilibili.com, twitter.com, x.com, tiktok.com, vimeo.com, instagram.com, twitch.tv. Outputs: MP4 video, MP3 audio, VTT subtitles with timestamps, TXT transcript, MD AI summary. Auto-installs uv, yt-dlp, ffmpeg. Python dependencies managed by uv."
---

# Video Summarizer

## Overview

Download videos from any platform and generate a complete resource package including:
- Original video file (mp4)
- Audio file (mp3)
- Subtitle file (with timestamps, vtt/srt format)
- Summary file (summary.md)

Supports all 1800+ websites supported by yt-dlp.

## Trigger Conditions

When the user:
- Provides a video link and asks for a summary
- Says "summarize this video", "what's in this video"
- Asks to "extract video content", "transcribe video"
- Says "download this video"
- Provides a link from YouTube/Bilibili/Twitter/Vimeo/TikTok etc.

## Supported Platforms

- YouTube (youtube.com, youtu.be)
- Bilibili (bilibili.com, b23.tv)
- Twitter/X (x.com, twitter.com)
- Vimeo (vimeo.com)
- TikTok (tiktok.com)
- Instagram (instagram.com)
- Twitch (twitch.tv)
- And 1800+ other platforms (all sites supported by yt-dlp)

## Output Structure

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
```

## Workflow

### Step 1: Install Dependencies

Run the install script to check and install all dependencies:

```bash
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.

### Step 2: Get Video Info and Create Output Directory

```bash
# 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"
```

### Step 3: Download Video and Audio

```bash
# 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"
```

### Step 4: Get Subtitles

**Priority order:**

1. **Try downloading manual subtitles (best quality)**
```bash
yt-dlp --write-subs --sub-lang zh,en,zh-Hans,zh-Hant --skip-download \
  -o "$OUTPUT_DIR/subtitle" "VIDEO_URL"
```

2. **Try downloading auto-generated subtitles**
```bash
yt-dlp --write-auto-subs --sub-lang zh,en --skip-download \
  -o "$OUTPUT_DIR/subtitle" "VIDEO_URL"
```

3. **Use faster-whisper transcription when no subtitles available**

```bash
uv run "$SKILL_DIR/scripts/parallel_transcribe.py" \
  --input "$OUTPUT_DIR/audio.mp3" \
  --output-dir "$OUTPUT_DIR" \
  --model small \
  --language auto
```

The script automatically:
- Splits long audio files at silence points
- Uses multiple CPU cores for parallel transcription
- Outputs both `subtitle.vtt` and `transcript.txt`

**Transcription 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 |

### Step 5: Generate Plain Text Transcript

If subtitles were downloaded (not transcribed), convert to plain text:

```bash
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
```

### Step 6: Generate Summary File

1. Read prompt template from `$SKILL_DIR/reference/summary-prompt.md`
2. Replace placeholders: `{{TITLE}}`, `{{PLATFORM}}`, `{{URL}}`, `{{DURATION}}`, `{{LANGUAGE}}`, `{{DOWNLOAD_TIME}}`, `{{TRANSCRIPT}}`
3. Generate summary and save to `$OUTPUT_DIR/summary.md`

## Platform-Specific Handling

### Bilibili
```bash
# Prioritize Chinese subtitles
yt-dlp --sub-lang zh-Hans,zh-Hant,zh ...
# If login required
yt-dlp --cookies-from-browser chrome "VIDEO_URL"
```

### Platforms Requiring Login
```bash
yt-dlp --cookies-from-browser chrome "VIDEO_URL"
# or firefox
yt-dlp --cookies-from-browser firefox "VIDEO_URL"
```

## Error Handling

### Cannot Get Subtitles
Use the parallel transcription script (Step 4, option 3).

### Video Too Long (>1 hour)
1. Ask user if they only need partial content
2. The parallel script handles long files automatically

### Unsupported Platform
```bash
yt-dlp --list-extractors | grep -i "platform-name"
```

## Notes

1. **Storage**: Files saved to `./downloads/` in current working directory
2. **Copyright**: For personal learning use only
3. **Network**: Some platforms may require proxy
4. **First Run**: Whisper model download required (~244MB for small)
5. **Parallel Processing**: Long audio (>60s) auto-splits at silence points