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video-metadata-inspector
by dkyazzentwatwa
My comprehensive, tested + audited, library of skills to use for ChatGPT.
⭐ 6🍴 0📅 Jan 20, 2026
SKILL.md
name: video-metadata-inspector description: Use when asked to inspect video file metadata, get video duration, resolution, codec information, frame rate, or bitrate.
Video Metadata Inspector
Extract and analyze comprehensive metadata from video files including duration, resolution, codec, frame rate, and technical specifications.
Purpose
Video metadata inspection for:
- Format verification and compatibility checking
- Quality assessment and validation
- Transcoding planning and optimization
- Video library cataloging
- Technical specification reports
Features
- Basic Info: Duration, resolution, frame rate, file size
- Codec Details: Video/audio codec, profile, bitrate
- Technical Specs: Aspect ratio, pixel format, sample rate
- Metadata: Title, artist, creation date, tags
- Batch Analysis: Process multiple files in one operation
- Export Formats: JSON, CSV, human-readable text
Quick Start
from video_metadata_inspector import VideoMetadataInspector
# Inspect single video
inspector = VideoMetadataInspector()
inspector.load('video.mp4')
metadata = inspector.get_metadata()
print(f"Duration: {metadata['duration_seconds']:.2f}s")
print(f"Resolution: {metadata['width']}x{metadata['height']}")
print(f"FPS: {metadata['fps']}")
# Export full report
inspector.export_report('report.json', format='json')
# Batch inspect directory
inspector.batch_inspect(
input_files=['video1.mp4', 'video2.mkv'],
output='metadata.csv',
format='csv'
)
CLI Usage
# Basic metadata
python video_metadata_inspector.py input.mp4
# Full technical details
python video_metadata_inspector.py input.mp4 --verbose
# Export to JSON
python video_metadata_inspector.py input.mp4 --output metadata.json --format json
# Batch inspect directory
python video_metadata_inspector.py *.mp4 --output metadata.csv --format csv
# Compare multiple videos
python video_metadata_inspector.py video1.mp4 video2.mp4 --compare
API Reference
VideoMetadataInspector
class VideoMetadataInspector:
def load(self, filepath: str) -> 'VideoMetadataInspector'
def get_metadata(self) -> Dict[str, Any]
def get_basic_info(self) -> Dict[str, Any]
def get_video_info(self) -> Dict[str, Any]
def get_audio_info(self) -> Dict[str, Any]
def get_format_info(self) -> Dict[str, Any]
def export_report(self, output: str, format: str = 'json') -> str
def batch_inspect(self, input_files: List[str], output: str = None,
format: str = 'csv') -> pd.DataFrame
def compare_videos(self, video_files: List[str]) -> pd.DataFrame
Metadata Categories
Basic Information
- Duration (seconds, formatted)
- Resolution (width × height)
- Frame rate (FPS)
- File size
- Aspect ratio
Video Stream
- Video codec (H.264, H.265, VP9, etc.)
- Codec profile and level
- Bitrate (kbps)
- Pixel format (yuv420p, etc.)
- Color space and range
Audio Stream
- Audio codec (AAC, MP3, Opus, etc.)
- Sample rate (Hz)
- Channels (mono, stereo, 5.1, etc.)
- Audio bitrate (kbps)
Container Format
- Container type (MP4, MKV, AVI, etc.)
- Creation date
- Metadata tags (title, artist, description)
- Number of streams
Use Cases
Format Verification:
inspector.load('video.mp4')
info = inspector.get_video_info()
if info['codec'] == 'h264' and info['width'] >= 1920:
print("✓ Meets requirements: 1080p H.264")
Transcoding Planning:
# Check if transcoding needed
metadata = inspector.get_metadata()
if metadata['video_codec'] != 'h265' or metadata['bitrate_kbps'] > 5000:
print("Transcode recommended")
Quality Assessment:
# Analyze video quality metrics
info = inspector.get_metadata()
quality_score = (
(info['width'] * info['height']) / 2073600 * 50 + # Resolution score
min(info['fps'] / 60, 1) * 25 + # Frame rate score
min(info['bitrate_kbps'] / 10000, 1) * 25 # Bitrate score
)
Common Checks
Is video 4K?
metadata['width'] >= 3840 and metadata['height'] >= 2160
Is video HDR?
'hdr' in metadata.get('color_space', '').lower()
Is audio stereo?
metadata['audio_channels'] == 2
Is codec modern?
metadata['video_codec'] in ['h265', 'vp9', 'av1']
Limitations
- Cannot extract corrupt/damaged video metadata
- Some proprietary formats may have limited support
- DRM-protected content cannot be analyzed
- Metadata extraction may be slow for very large files
- Requires FFmpeg/FFprobe for full codec details
Score
Total Score
55/100
Based on repository quality metrics
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