Short Drama Publisher (短剧自动化发布)

Automated short drama promotion video workflow, inspired by Strawberry TV model:

1. 📥 Download drama content from MoboBoost
2. 🎯 AI-powered highlight detection (scene changes, audio peaks, subtitle emotion)
3. ✂️ Clip 15-second vertical videos with white English title overlay
4. 📤 Auto-publish to Facebook

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Prerequisites

System Dependencies

# macOS
brew install ffmpeg

# Python dependencies
pip install playwright opencv-python librosa numpy pyyaml
playwright install chromium

Credentials Setup

1. MoboBoost Cookies
2. Login to https://ckoc.cdreader.com
3. Export cookies using browser extension (e.g., "EditThisCookie")

4. Save as config/moboboost_cookies.json

5. Facebook Cookies

6. Login to Facebook
7. Export cookies using browser extension
8. Save as config/facebook_cookies.json

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Usage

Full Automated Workflow

python scripts/daily_workflow.py

Individual Modules

Download content:

python scripts/moboboost_downloader.py --drama-code 613815

Detect highlights:

python scripts/highlight_detector.py --input data/downloads/video.mp4

Clip video:

python scripts/video_editor.py --input video.mp4 --start 01:23 --title "Drama Name"

Publish to Facebook:

python scripts/facebook_publisher.py --video data/outputs/clip.mp4 --drama-code 613815 --drama-name "DramaName"

Daily Cron Job

# Run daily at 9am
0 9 * * * cd /path/to/short-drama-publisher && python scripts/daily_workflow.py >> logs/cron.log 2>&1

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Configuration

settings.yaml

# Video settings
video:
  duration: 15          # Clip duration (seconds)
  width: 1080           # Width
  height: 1920          # Height (9:16 vertical)

# Text overlay settings
text_overlay:
  font: "Arial-Bold"
  size_ratio: 0.05      # Font size as ratio of video width
  color: "#FFFFFF"
  border_color: "#000000"
  border_width: 2
  position_y: 0.75      # Vertical position (ratio from top)

# AI highlight detection weights
highlight_weights:
  scene_change: 0.30
  audio_peak: 0.25
  subtitle_emotion: 0.25
  motion_intensity: 0.20

# Publishing settings
publishing:
  videos_per_day: 3     # Number of videos per day
  interval_minutes: 120 # Interval between posts (minutes)

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Directory Structure

short-drama-publisher/
├── SKILL.md                    # This file
├── config/
│   ├── settings.yaml           # Configuration
│   ├── moboboost_cookies.json  # MoboBoost credentials
│   └── facebook_cookies.json   # Facebook credentials
├── scripts/
│   ├── moboboost_downloader.py # Content downloader
│   ├── highlight_detector.py   # AI highlight detection
│   ├── video_editor.py         # Video clipping
│   ├── facebook_publisher.py   # Facebook publisher
│   └── daily_workflow.py       # Main workflow
├── data/
│   ├── downloads/              # Raw downloaded content
│   ├── outputs/                # Clipped videos
│   └── history.json            # Publishing history
├── fonts/                      # Font files
└── logs/                       # Log files

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AI Highlight Detection

The highlight detector uses multiple signals to find the most engaging moments:

Signal	Weight	Method
Scene Change	30%	OpenCV frame-by-frame difference analysis
Audio Peak	25%	Librosa audio amplitude analysis
Subtitle Emotion	25%	Text sentiment analysis on subtitles
Motion Intensity	20%	Optical flow magnitude calculation

Each frame gets a composite score, and the highest-scoring 15-second segment is selected.

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Important Notes

[!WARNING] - MoboBoost and Facebook websites may update, requiring script adjustments - Recommend 1-3 videos per day to simulate organic posting rhythm - Ensure you have rights to use MoboBoost content for promotion - Cookie-based auth may expire; re-export periodically