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Video Engineer

Purpose

Provides expertise in video processing, encoding, streaming, and infrastructure. Specializes in FFmpeg automation, adaptive streaming protocols, real-time communication, and building scalable video delivery systems.

When to Use

• Implementing video encoding and transcoding pipelines
• Setting up HLS or DASH streaming infrastructure
• Building WebRTC applications for real-time video
• Automating video processing with FFmpeg
• Optimizing video quality and compression
• Creating video thumbnails and previews
• Implementing video analytics and metadata extraction
• Building video player integrations

Quick Start

Invoke this skill when:

• Implementing video encoding and transcoding pipelines
• Setting up HLS or DASH streaming infrastructure
• Building WebRTC applications for real-time video
• Automating video processing with FFmpeg
• Optimizing video quality and compression

Do NOT invoke when:

• Building general web applications → use fullstack-developer
• Creating animated GIFs → use slack-gif-creator
• Media file analysis only → use multimodal-analysis
• Image processing without video → use appropriate skill

Decision Framework

Video Engineering Task?
├── On-Demand Streaming → HLS/DASH with adaptive bitrate
├── Live Streaming → Low-latency HLS or WebRTC
├── Real-Time Communication → WebRTC with STUN/TURN
├── Batch Processing → FFmpeg pipeline automation
├── Quality Optimization → Codec selection + encoding params
└── Video Analytics → Metadata extraction + scene detection

Core Workflows

1. Adaptive Streaming Setup

1. Analyze source video specifications
2. Define quality ladder (resolutions, bitrates)
3. Configure encoder settings per quality level
4. Generate HLS/DASH manifests
5. Set up CDN for segment delivery
6. Implement player with ABR support
7. Monitor playback quality metrics

2. FFmpeg Processing Pipeline

1. Define input sources and formats
2. Build filter graph for transformations
3. Configure encoding parameters
4. Handle audio/video synchronization
5. Implement error handling and retries
6. Parallelize for throughput
7. Validate output quality

3. WebRTC Implementation

1. Set up signaling server
2. Configure STUN/TURN servers
3. Implement peer connection handling
4. Manage media tracks and streams
5. Handle network adaptation (simulcast, SVC)
6. Implement recording if needed
7. Monitor connection quality metrics

Best Practices

• Use hardware encoding (NVENC, QSV) when available for speed
• Implement adaptive bitrate for variable network conditions
• Pre-generate all quality levels for on-demand content
• Use appropriate codecs for use case (H.264 compatibility, H.265/AV1 efficiency)
• Set keyframe intervals appropriate for seeking and ABR switching
• Monitor and alert on encoding queue depth and latency

Anti-Patterns

• Single bitrate streaming → Always use adaptive bitrate
• Ignoring audio sync → Verify A/V alignment after processing
• Oversized segments → Keep HLS segments 2-10 seconds
• No error handling → FFmpeg can fail; implement retries
• Hardcoded paths → Parameterize for different environments

Weekly Installs

75

Repository

404kidwiz/claud…e-skills

GitHub Stars

42

First Seen

Jan 24, 2026

Security Audits

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Installed on

opencode64

gemini-cli58

codex57

cursor53

claude-code53

github-copilot50