plugins/viral-video-master/skills/viral-video-long-form/SKILL.md
Complete YouTube long-form video optimization for maximum watch time, SEO, and viral potential. PROACTIVELY activate for: (1) YouTube video strategy, (2) Long-form content planning, (3) Watch time optimization, (4) YouTube SEO, (5) Thumbnail design strategy, (6) Audience retention techniques, (7) YouTube monetization, (8) Connected TV optimization, (9) YouTube algorithm understanding. Provides: Video length optimization, thumbnail best practices, SEO strategies, retention techniques, monetization guidelines, and analytics interpretation.
npx skillsauth add JosiahSiegel/claude-plugin-marketplace viral-video-long-formInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Complete guide to creating viral long-form content primarily for YouTube, with strategies for watch time optimization, SEO, thumbnails, and audience building.
| Duration | Performance | Best For | Notes | |----------|-------------|----------|-------| | 7-15 minutes | Sweet spot | Most content | Ideal for tutorials, reviews | | 8-9 minutes | Best for search | SEO-focused | Consistently performs best in rankings | | 8+ minutes | More ads | Monetization | Enables mid-roll placements | | 10-30 minutes | Effective range | In-depth topics | Documentary, education | | 40+ minutes | Extended content | Deep dives | Podcast, interviews |
| Specification | Recommended | |---------------|-------------| | Aspect ratio | 16:9 | | Resolution | 1920x1080 (1080p) or 3840x2160 (4K) | | Frame rate | 24, 30, or 60 fps | | File format | MP4 (H.264/H.265) | | Audio | AAC, 48kHz, stereo or higher |
| Signal | Weight | What It Measures | |--------|--------|------------------| | Watch time | Highest | Total minutes watched | | Audience retention | Very High | Percentage of video watched | | Click-through rate (CTR) | Very High | Clicks / Impressions | | Session time | High | Time viewer spends on YouTube after | | Engagement | Medium | Likes, comments, shares, saves |
Discovery Phase:
Recommendation Phase:
Maximize Watch Time:
Optimize CTR:
Increase Session Time:
Unlike short-form's 1.3-second rule, long-form allows 5-10 seconds for hooks, but the principles remain:
Hook Components:
Preview Hook: "In this video, I'm going to show you [result]. By the end, you'll know [specific outcome]."
Curiosity Hook: "What I'm about to share changed everything I thought I knew about [topic]..."
Result Hook: [Show the end result] "This is what we're building today, and I'll show you exactly how."
Story Hook: "Three months ago, I made a mistake that cost me [consequence]. Here's what I learned..."
Problem Hook: "If you've ever struggled with [problem], you're not alone. Here's what actually works."
| Metric | Impact | |--------|--------| | Videos with custom thumbnails | 90% of top performers | | CTR with custom thumbnails | 60-70% higher | | CTR with emotional faces | 20-30% higher | | High contrast visibility | 20-30% increase |
Face and Emotion:
Text Optimization:
Color Strategy: | Color | Psychology | Use For | |-------|------------|---------| | Red/Orange | Urgency, excitement | Action, entertainment | | Blue | Trust, calm | Educational, tech | | Yellow | Attention, optimism | Happy content, tips | | Green | Growth, money | Finance, health |
Composition:
| Statistic | Value | |-----------|-------| | Google searches with video snippets | 25%+ | | Top-ranking videos average age | 29 months | | Top-ranking videos with captions | 94% | | View boost from Google ranking | 2-5x | | Best performing length in search | 8-9 minutes |
Best Practices:
Title Formula:
[Keyword] + [Benefit/Result] + [Specificity]
Examples:
Structure:
[Hook - First 2-3 lines visible without expansion]
Primary keyword in first 25 words
Clear value proposition
[Body - 150-250 words total]
Semantic keywords naturally included
Timestamps/chapters
Resource links
[Footer]
Social links
CTA
Related video links
Key Guidelines:
Tag Strategy:
Keyword Research:
| Metric | Value | Impact | |--------|-------|--------| | 2025 average retention | 23.7% | Baseline | | Videos surpassing 50% | 16.8% | Above average | | Videos reaching final 10 seconds | 16% | Excellent | | 70%+ retention in first 30 seconds | Much higher ranking | Critical |
10% retention improvement = 25%+ impression increase
Eliminate These:
Pattern Interrupts (Every 30-60 seconds):
Structural Elements:
Visual Variety:
Why Chapters Matter:
Format:
0:00 Introduction
1:23 Chapter Title
4:56 Another Chapter
...
Best Practices:
Watch time is the single most important metric for YouTube long-form success. It determines:
Content Structure:
Pacing Guidelines:
Series and Playlists:
Shorts + Long-form = 41% faster channel growth
Teaser Strategy:
Audience Building:
Content Repurposing:
Detailed long-form YouTube optimization for monetization, Connected TV viewing, analytics / metrics interpretation, and production-quality guidelines lives in references/monetization-tv-analytics-production.md. Load that reference when tuning revenue, TV viewing, measurement, or production standards beyond hooks / retention / discovery.
development
This skill should be used when the user asks to train, debug, scale, or improve ML models. PROACTIVELY activate for: (1) PyTorch, TensorFlow/Keras, JAX, Flax, Hugging Face Trainer/Accelerate training loops, (2) distributed training, DDP/FSDP/DeepSpeed, TPU/GPU setup, (3) mixed precision AMP/bf16, gradient accumulation, checkpointing, seeding, (4) overfitting, imbalance, loss functions, regularization, LR schedules, warmup, (5) memory optimization, gradient checkpointing, offloading, quantization-aware training. Provides: reproducible training best practices across deep learning and classical ML.
development
This skill should be used when the user asks to productionize, track, version, govern, monitor, or automate ML systems. PROACTIVELY activate for: (1) MLflow, Weights & Biases, Neptune, Comet, ClearML experiment tracking, (2) model registry, model versioning, artifact lineage, reproducibility, (3) Kubeflow, SageMaker Pipelines, Vertex AI Pipelines, Azure ML pipelines, Databricks workflows, (4) CI/CD, continuous training/evaluation, A/B tests, canary/shadow deployments, (5) drift detection, model monitoring, data validation, responsible AI governance. Provides: end-to-end MLOps architecture and operational safeguards.
development
This skill should be used when the user asks to optimize, export, serve, compress, or accelerate ML inference. PROACTIVELY activate for: (1) latency, throughput, p95/p99, batching, concurrency, KV cache, memory, or cost issues, (2) quantization INT8/INT4, GPTQ, AWQ, bitsandbytes, pruning, sparsity, distillation, (3) ONNX export, ONNX Runtime, TensorRT, TorchScript, torch.compile, XLA, OpenVINO, Core ML, TFLite, (4) Triton, TorchServe, TF Serving, BentoML, Seldon, KServe configuration, (5) edge deployment, CPU/GPU/TPU/Inferentia serving. Provides: hardware-aware inference optimization and safe benchmarking.
testing
This skill should be used when the user asks to tune hyperparameters, run sweeps, optimize search spaces, or use AutoML. PROACTIVELY activate for: (1) Optuna, Ray Tune, FLAML, AutoGluon, Hyperopt, Nevergrad, KerasTuner, W&B sweeps, (2) grid search, random search, Bayesian optimization, TPE, Gaussian processes, evolutionary search, (3) ASHA, Hyperband, successive halving, multi-fidelity optimization, population-based training, (4) learning-rate finder, batch-size search, early stopping, pruning, (5) reproducible sweep design and experiment analysis. Provides: budget-aware hyperparameter search strategy.