---
name: auto-clipper
description: AI-powered video clipper - Convert long videos into viral Shorts/TikToks/Reels automatically
domain: content
tags:
- auto
- clipper
- content-creation
- digital-content
- media
- video
dependencies: "- faster-whisper\n  - textblob\n  - vadersentiment\n  - moviepy\n  - opencv-python\n  - ffmpeg-python\n  -\
  \ customtkinter\n"
---


# Auto Clipper Indonesia 🎬
## When to Use

**Trigger phrases:**
- "auto clipper"
- "Help me with auto clipper"

**Use cases:**
- When the task matches this skill's domain expertise

**When NOT to use:**
- For tasks outside this skill's scope


**Production-ready** AI-powered video clipper untuk content creator Indonesia.

## 🎯 Features

- **AI Transcription** - local Whisper model (Indonesian + English)
- **Golden Moment Detection** - automaticamente detect best clips
- **Smart Reframe** - 9:16 vertical conversion dengan face tracking
- **Subtitle Burn** - Auto-generate dan burn subtitles
- **Batch Processing** - Process unlimited clips
- **Progress Tracking** - Real-time status updates

## 📦 Files

```
auto-clipper/
├── SKILL.md              # This file
├── config.json           # Configuration
├── auto_clipper.py       # Main skill wrapper
└── core/                 # Core modules (from project)
    ├── __init__.py
    ├── video_analyzer.py
    ├── clip_engine.py
    ├── reframe_engine.py
    ├── subtitle_engine.py
    └── workflow.py
```

## 🔧 Installation

- Configure auto, automatically, clipper, convert, into settings before first use
- Review output quality and adjust parameters
- Monitor performance metrics during execution
- Document custom configurations for team reference
- Schedule regular runs for consistent results


### Install Dependencies
```bash
pip install faster-whisper textblob vaderSentiment
pip install moviepy opencv-python ffmpeg-python
pip install customtkinter pillow requests
```

### Install FFmpeg (Required)
```bash
# Linux
sudo apt install ffmpeg

# macOS
brew install ffmpeg

# Windows
# Download from https://ffmpeg.org/download.html
# Add to PATH
```

## 📖 Usage

- Configure auto, automatically, clipper, convert, into settings before first use
- Review output quality and adjust parameters
- Monitor performance metrics during execution
- Document custom configurations for team reference
- Schedule regular runs for consistent results


### Basic Usage
```python
from auto_clipper import AutoClipperSkill

# Initialize
skill = AutoClipperSkill()

# Full workflow (analyze + process + export)
results = skill.process_video(
    video_path="path/to/video.mp4",
    num_clips=10,
    clip_duration=30
)
print(f"Created {len(results)} clips")
```

### Advanced Usage
```python
# With custom configuration
skill = AutoClipperSkill(config={
    "clip_duration": 45,
    "output_resolution": "1080p",
    "num_clips": 15,
    "add_subtitles": True
})

# Analyze only - get golden moments
moments = skill.analyze_video("video.mp4")
print(f"Found {len(moments)} golden moments")

# Process specific clips
results = skill.process_clips(
    video_path="video.mp4",
    clip_indices=[0, 2, 5],  # Process specific moments
    add_subtitles=True
)

# Export with subtitle style
results = skill.export(
    video_path="video.mp4",
    clips=selected_moments,
    subtitle_style="social",
    output_resolution="1080p"
)
```

### CLI Usage
```bash
# Process video
python auto_clipper.py --video video.mp4 --clips 10 --duration 30

# Analyze video only
python auto_clipper.py --video video.mp4 --analyze

# With subtitles
python auto_clipper.py --video video.mp4 --subtitles --style social
```

## ⚙️ Configuration

Edit `config.json`:
```json
{
  "clip_duration": 30,
  "output_resolution": "720p",
  "whisper_model": "base",
  "num_clips": 10,
  "add_subtitles": true,
  "output_format": "mp4",
  "output_directory": "./output"
}
```

## 🎨 Subtitle Styles

```python
# Clean - Minimal subtitles
style = "clean"

# Bold - High attention
style = "bold"

# Social - Large, for mobile
style = "social"

# TikTok - Top position
style = "tiktok"
```

## 📊 Output

Results dalam format:
```python
{
    "clip_id": "clip_001",
    "status": "success",
    "output_path": "./output/clip_001.mp4",
    "start_time": 30.5,
    "end_time": 60.2,
    "duration": 29.7,
    "size_mb": 12.5,
    "original_text": "Hook: This blew my mind..."
}
```

## 🛠️ Troubleshooting

- Configure auto, automatically, clipper, convert, into settings before first use
- Review output quality and adjust parameters
- Monitor performance metrics during execution
- Document custom configurations for team reference
- Schedule regular runs for consistent results


### Whisper Installation Failed?

```bash
# Windows
pip install faster-whisper --no-build-isolation

# Linux/macOS
sudo apt install libasound2-dev  # For audio support
pip install faster-whisper
```

### FFmpeg Not Found?

```bash
# Verify installation
ffmpeg -version

# Add to PATH (Windows)
setx PATH "%PATH%;C:\ffmpeg\bin"

# macOS
echo 'export PATH="/usr/local/opt/ffmpeg/bin:$PATH"' >> ~/.zshrc
```

### Memory Issues?

Use smaller Whisper model:
```python
skill = AutoClipperSkill(config={"whisper_model": "tiny"})
```

### Processing Slow?

Optimize settings:
```json
{
  "output_resolution": "720p",
  "whisper_model": "tiny",
  "clip_duration": 30
}
```

## 📈 Performance

| Setting | Speed | Quality |
|---------|-------|---------|
| Whisper tiny + 720p | ⚡ Fast | Good |
| Whisper base + 720p | 🚀 Normal | Better |
| Whisper small + 1080p | 🚶 Slow | Best |

## ⚠️ Requirements

- **OS**: Windows 10/11, macOS, Linux
- **Python**: 3.11+
- **Memory**: 4GB RAM minimum (8GB recommended)
- **Storage**: 2GB for dependencies
- **FFmpeg**: Required for video processing

## 🚀 Next Updates

Planned improvements:
- [ ] Distribution automation (TikTok/IG/YT)
- [ ] Face beautification filter
- [ ] Background music addition
- [ ] Template library
- [ ] Cloud rendering option

## 📝 License

Proprietary - BerkahKarya

## 💰 Support

Join our community:
- Telegram: @berkahkarya
- Website: berkahkarya.id

---

**BerkahKarya** ⚡ | Auto Clipper Indonesia

## How to Use

1. Define content goal (traffic, engagement, conversion, brand awareness)
2. Research target audience pain points and search intent
3. Generate content using appropriate AI tools
4. Edit and humanize output for authenticity
5. Optimize for target platform (SEO, hashtags, format)
6. Schedule and distribute across channels
7. Measure performance and iterate

## When NOT to Use

- Task is about content strategy, not creation (use strategy skills)
- Task is about content distribution (use distribution skills)
- You need to analyze content performance (use analytics skills)
- Task is about content moderation (use moderation tools)
- You don't have content guidelines
- Task requires domain expertise (consult experts)


## Red Flags

- **AI-generated content sounds robotic**: Always run through humanizer before publishing
- **Engagement dropping week-over-week**: Content fatigue or algorithm change — vary formats
- **Duplicate content across platforms**: Adapt content per platform, don't just cross-post
- **No content calendar**: Sporadic posting kills audience retention
- **Ignoring analytics**: Content without measurement is just publishing, not marketing

## Verification

- Check readability score (target grade 8 or below for general audiences)
- Verify all images have alt text and proper dimensions per platform
- Confirm links work and point to correct destinations
- Test video/audio quality before publishing
- Validate content renders correctly on mobile devices

## Overview

> Section content — see SKILL.md body for full details.