media-expert
Expert-level media production, content management, streaming, broadcasting, and media technology systems. Use when the user mentions video, streaming, broadcast, CMS, or production, or when the task involves Media Production, Streaming and Broadcasting, Technologies, or Standards and Protocols.
How do I install this agent skill?
npx skills add https://github.com/personamanagmentlayer/pcl --skill media-expertIs this agent skill safe to install?
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The media-expert skill provides technical documentation and simulated Python implementations for media production, streaming, and broadcasting workflows. The analysis found no malicious code, data exfiltration, or obfuscation. All external links point to legitimate industry standards and resources.
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Risk: LOW · No issues
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1/1 file flagged
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1 finding · Score: 86/100
What does this agent skill do?
Media Expert
Expert guidance for media production, content management systems, video streaming, broadcasting systems, and modern media technology solutions.
Core Concepts
Media Production
- Video production workflows
- Audio production and mixing
- Post-production and editing
- Visual effects (VFX)
- Color grading and correction
- Animation and motion graphics
- Live production
Streaming and Broadcasting
- Video streaming platforms
- Content Delivery Networks (CDN)
- Adaptive bitrate streaming
- Live broadcasting
- OTT (Over-the-Top) platforms
- Digital rights management (DRM)
- Transcoding and encoding
Technologies
- Media Asset Management (MAM)
- Digital Asset Management (DAM)
- Broadcast automation
- IP-based media production
- Cloud production workflows
- AI for content analysis
- Virtual production
Standards and Protocols
- SMPTE standards
- HLS (HTTP Live Streaming)
- DASH (Dynamic Adaptive Streaming over HTTP)
- RTMP/RTSP protocols
- NDI (Network Device Interface)
- MXF (Material Exchange Format)
- Metadata standards (Dublin Core, IPTC)
Video Streaming Platform
class VideoStreamingPlatform:
"""Video streaming and delivery system"""
def __init__(self):
self.streams = {}
self.viewers = {}
self.cdn_nodes = {}
def start_live_stream(self, stream_data: dict) -> dict:
"""Start live video stream"""
stream_id = self._generate_stream_id()
stream = {
'stream_id': stream_id,
'title': stream_data['title'],
'description': stream_data.get('description', ''),
'streamer_id': stream_data['streamer_id'],
'status': 'live',
'started_at': datetime.now(),
'viewer_count': 0,
'peak_viewers': 0,
'ingest_url': f'rtmp://ingest.example.com/live/{stream_id}',
'playback_urls': {
'hls': f'https://cdn.example.com/live/{stream_id}/playlist.m3u8',
'dash': f'https://cdn.example.com/live/{stream_id}/manifest.mpd'
},
'quality_profiles': ['1080p', '720p', '480p', '360p']
}
self.streams[stream_id] = stream
return stream
def generate_adaptive_bitrate_manifest(self, asset_id: str) -> dict:
"""Generate ABR manifest for adaptive streaming"""
# Generate HLS manifest
hls_variants = [
{
'bandwidth': 5000000, # 5 Mbps
'resolution': '1920x1080',
'codecs': 'avc1.640028,mp4a.40.2',
'url': f'1080p/playlist.m3u8'
},
{
'bandwidth': 2800000, # 2.8 Mbps
'resolution': '1280x720',
'codecs': 'avc1.64001f,mp4a.40.2',
'url': f'720p/playlist.m3u8'
},
{
'bandwidth': 1400000, # 1.4 Mbps
'resolution': '854x480',
'codecs': 'avc1.64001e,mp4a.40.2',
'url': f'480p/playlist.m3u8'
},
{
'bandwidth': 800000, # 800 Kbps
'resolution': '640x360',
'codecs': 'avc1.64001e,mp4a.40.2',
'url': f'360p/playlist.m3u8'
}
]
return {
'asset_id': asset_id,
'protocol': 'hls',
'master_playlist_url': f'https://cdn.example.com/vod/{asset_id}/master.m3u8',
'variants': hls_variants
}
def track_viewer_metrics(self, stream_id: str, viewer_id: str) -> dict:
"""Track viewer engagement metrics"""
metrics = {
'stream_id': stream_id,
'viewer_id': viewer_id,
'watch_time_seconds': 3600,
'buffer_events': 2,
'average_bitrate': 3500000,
'quality_switches': 5,
'playback_start_time_ms': 1200,
'errors': 0,
'device_type': 'desktop',
'browser': 'chrome'
}
# Calculate Quality of Experience (QoE)
qoe_score = self._calculate_qoe(metrics)
metrics['qoe_score'] = qoe_score
return metrics
def _calculate_qoe(self, metrics: dict) -> float:
"""Calculate Quality of Experience score"""
score = 100.0
# Penalize buffering
score -= metrics['buffer_events'] * 5
# Penalize startup time
if metrics['playback_start_time_ms'] > 2000:
score -= 10
# Penalize errors
score -= metrics['errors'] * 15
return max(0.0, score)
def implement_drm(self, asset_id: str, drm_config: dict) -> dict:
"""Implement Digital Rights Management"""
drm = {
'asset_id': asset_id,
'drm_systems': {
'widevine': {
'license_url': 'https://license.example.com/widevine',
'supported_levels': ['L1', 'L3']
},
'fairplay': {
'certificate_url': 'https://license.example.com/fairplay/cert',
'license_url': 'https://license.example.com/fairplay/license'
},
'playready': {
'license_url': 'https://license.example.com/playready'
}
},
'encryption': 'AES-128-CTR',
'key_rotation_interval': 3600 # seconds
}
return drm
def optimize_cdn_delivery(self, asset_id: str, viewer_location: tuple) -> dict:
"""Optimize CDN delivery based on viewer location"""
# Find nearest CDN edge node
nearest_node = self._find_nearest_cdn_node(viewer_location)
return {
'asset_id': asset_id,
'cdn_node': nearest_node['node_id'],
'cdn_location': nearest_node['location'],
'distance_km': nearest_node['distance'],
'estimated_latency_ms': nearest_node['latency'],
'delivery_url': f"https://{nearest_node['node_id']}.cdn.example.com/{asset_id}"
}
def _find_nearest_cdn_node(self, viewer_location: tuple) -> dict:
"""Find nearest CDN edge node to viewer"""
# Would calculate actual distances to CDN nodes
return {
'node_id': 'edge-us-east-1',
'location': 'Virginia, USA',
'distance': 250, # km
'latency': 15 # ms
}
def _generate_stream_id(self) -> str:
import uuid
return f"STREAM-{uuid.uuid4().hex[:8].upper()}"
Broadcast Automation
class BroadcastAutomationSystem:
"""Broadcast scheduling and automation"""
def __init__(self):
self.schedule = []
self.playlists = {}
def create_broadcast_schedule(self, channel: str, date: datetime, programming: List[dict]) -> dict:
"""Create daily broadcast schedule"""
schedule_items = []
current_time = date.replace(hour=0, minute=0, second=0)
for program in programming:
item = {
'channel': channel,
'start_time': current_time,
'end_time': current_time + timedelta(seconds=program['duration']),
'program_title': program['title'],
'asset_id': program['asset_id'],
'type': program['type'], # 'program', 'commercial', 'filler'
'metadata': program.get('metadata', {})
}
schedule_items.append(item)
current_time = item['end_time']
self.schedule.extend(schedule_items)
return {
'channel': channel,
'date': date.date().isoformat(),
'total_items': len(schedule_items),
'total_duration': (schedule_items[-1]['end_time'] - schedule_items[0]['start_time']).seconds,
'schedule': schedule_items[:5] # Return first 5 items
}
def generate_playlist(self, schedule_id: str) -> dict:
"""Generate playout playlist"""
# Convert schedule to playout format
playlist = {
'playlist_id': self._generate_playlist_id(),
'format': 'xml', # or 'json'
'items': []
}
return playlist
def monitor_broadcast(self, channel: str) -> dict:
"""Monitor live broadcast status"""
status = {
'channel': channel,
'on_air': True,
'current_program': 'Evening News',
'time_code': '00:15:32',
'next_program': 'Sports Tonight',
'next_program_in': 2728, # seconds
'signal_quality': {
'video_ok': True,
'audio_ok': True,
'sync_ok': True
},
'alarms': []
}
return status
def _generate_playlist_id(self) -> str:
import uuid
return f"PLAY-{uuid.uuid4().hex[:8].upper()}"
Best Practices
Media Production
- Use standardized workflows
- Implement version control
- Maintain proper backups
- Use collaborative tools
- Implement quality control
- Document production processes
- Use industry-standard formats
Content Management
- Implement robust metadata schema
- Use consistent naming conventions
- Enable full-text search
- Implement access controls
- Maintain audit trails
- Use automated workflows
- Implement archival policies
Streaming Delivery
- Use adaptive bitrate streaming
- Implement CDN for global delivery
- Monitor QoE metrics
- Optimize for mobile devices
- Implement DRM when required
- Use low-latency protocols for live
- Monitor buffer ratios
Broadcasting
- Implement redundant systems
- Automate scheduling
- Monitor signal quality
- Maintain emergency protocols
- Use backup playout systems
- Implement proper logging
- Conduct regular testing
Anti-Patterns
❌ No backup systems ❌ Poor metadata management ❌ Single bitrate streaming ❌ No CDN implementation ❌ Ignoring QoE metrics ❌ Manual scheduling processes ❌ No DRM for premium content ❌ Poor asset organization ❌ No disaster recovery plan
Reference Documentation
Detailed material lives alongside this skill and is read on demand:
Resources
- SMPTE: https://www.smpte.org/
- Streaming Media: https://www.streamingmedia.com/
- NAB (National Association of Broadcasters): https://www.nab.org/
- EBU (European Broadcasting Union): https://www.ebu.ch/
- FFmpeg: https://ffmpeg.org/
- Video.js: https://videojs.com/
- OTT Standards: https://www.ott-standards.org/
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/personamanagmentlayer/pcl/media-expert">View media-expert on skillZs</a>