skills/ai-video-production-master/SKILL.md
Expert in script-to-video production pipelines for Apple Silicon Macs. Specializes in hybrid local/cloud workflows, LoRA training for character consistency, motion graphics generation, and artist commissioning. Activate on 'AI video production', 'script to video', 'video generation pipeline', 'character consistency', 'LoRA training', 'cloud GPU', 'motion graphics', 'Wan I2V', 'InVideo alternative'. NOT for real-time video editing, video compositing (use DaVinci/Premiere), audio production, or 3D modeling (use Blender/Maya).
npx skillsauth add curiositech/windags-skills ai-video-production-masterInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Expert in script-to-video production pipelines for Apple Silicon Macs. Specializes in hybrid local/cloud workflows, style consistency, and motion graphics generation.
Script Analysis:
├── Content Type = Educational/Corporate/Documentary
│ ├── Budget < $50/month → Stock Footage Assembly (InVideo-style)
│ └── Budget > $50/month → Stock + T2V Hybrid
├── Content Type = Creative/Artistic/Abstract
│ ├── Timeline < 2 days → Sora/Runway T2V
│ └── Timeline > 2 days → Custom I2V with LoRA training
└── Content Type = Brand/Character-focused
├── Existing assets available → I2V animation pipeline
└── No assets → Commission artists → I2V pipeline
Quality vs. Cost Decision:
├── Professional deliverable needed
│ ├── Use Sora/Runway Gen-3 (premium T2V)
│ └── Commission custom artwork for I2V
├── Prototype/test content
│ ├── Use stock footage + free T2V models
│ └── Local ComfyUI I2V generation
└── High volume production
├── Cloud batch processing (Vast.ai)
└── Automated stock footage workflows
Error Recovery Tree:
├── Quality fails at T2V generation
│ ├── Switch to stock footage + motion graphics overlay
│ └── Fallback to I2V with commissioned artwork
├── Cloud GPU timeout/failure
│ ├── Retry with different provider (Vast.ai → RunPod)
│ └── Switch to local processing with extended timeline
└── Style consistency breaks
├── Retrain LoRA with more reference images
└── Use IPAdapter + consistent prompt structure
| Shot Count | Complexity | Budget | Recommendation | |------------|------------|--------|----------------| | 1-5 | Simple | Any | Local M4 Max | | 6-20 | Medium | <$10 | Stock footage | | 6-20 | High | >$10 | Cloud GPU batch | | 20+ | Any | Any | Cloud GPU required |
Symptoms: Inconsistent frame rates, stuttering motion, temporal artifacts Diagnosis: Mismatched FPS settings or insufficient motion guidance Fix: Set consistent 24fps pipeline, add motion strength controls, use higher guidance scale (7-9) Detection Rule: If temporal consistency score < 0.7 or frame delta > 0.3, apply motion stabilization
Symptoms: Character appearance changes between shots, style inconsistency Diagnosis: Insufficient reference conditioning or LoRA overfitting Fix: Retrain LoRA with 15-20 reference images, use IPAdapter for face consistency Detection Rule: If character similarity score < 0.8 between consecutive shots, halt and retrain
Symptoms: Cloud GPU bills exceed budget by >200%, slow iteration cycles Diagnosis: No cost monitoring or inefficient batch sizing Fix: Set hard limits in cloud scripts, optimize batch sizes, use spot instances Detection Rule: If cost-per-minute exceeds $0.50 or iteration time > 15min, switch to local processing
Symptoms: Lip sync drift, audio-visual timing mismatches Diagnosis: Variable generation times affecting audio alignment Fix: Generate all video first, then align audio in post with markers Detection Rule: If audio offset > 200ms from video markers, re-align with FFmpeg
Symptoms: Too many generation options, analysis paralysis, project stalls Diagnosis: Over-optimization without testing simple approaches first Fix: Always start with stock footage proof-of-concept, iterate to complexity Detection Rule: If project planning > 2 hours without generated content, default to stock footage
Input: 3-minute script about quantum computing basics
Decision Process:
Execution:
# Step 1: Generate shot list from script
python scripts/script_analyzer.py --script quantum_script.txt
# Output: 12 shots identified, 8 require stock footage, 4 need motion graphics
# Step 2: Source stock footage
python scripts/stock_video_generator.py --shots_file shots.json --style documentary
# Selected: Laboratory footage, abstract tech visuals, clean backgrounds
# Step 3: Generate motion graphics for complex concepts
python scripts/motion_graphics_generator.py --type data_viz --concept "quantum_states"
# Created: Animated diagrams for superposition, entanglement
# Step 4: Assembly and sync
python scripts/video_assembler.py --footage stock_clips/ --graphics motion/ --audio narration.wav
Expert vs. Novice:
Final output: 3:15 video, cost $0 (free stock), 45 minutes total production time
Video production complete when ALL conditions met:
This skill should NOT be used for:
physics-rendering-expert skillsound-engineer skill for mixing, mastering, sound designphysics-rendering-expert skillHandoff triggers:
physics-rendering-expertsound-engineertools
Building resilient distributed systems with circuit breakers, retries with full-jitter exponential backoff, retry budgets (per-request 3-attempt + per-client 10% ratio per Google SRE), deadline propagation, and the cascading-failure math (4 layers × 3 retries = 64x amplification). Grounded in Resilience4j, Microsoft Cloud Patterns, AWS Architecture Blog (Marc Brooker), and Google SRE Book.
testing
Designing HTTP cache headers that work correctly across browsers, CDNs, and shared proxies — `Cache-Control` directives per RFC 9111, `stale-while-revalidate` and `stale-if-error` per RFC 5861, the Vary header for varying responses, and surrogate keys for tag-based purging. Grounded in IETF RFCs and Cloudflare/Fastly docs.
development
Use when designing or fixing a Content Security Policy on a real site, choosing between nonce-based and hash-based CSP, adding strict-dynamic, debugging "Refused to execute inline script" errors, deploying CSP in report-only mode first, configuring report-to / report-uri, or auditing an existing policy for unsafe-inline / unsafe-eval / wildcards. Triggers: "CSP blocks legitimate inline script", strict-dynamic, nonce-{RANDOM}, sha256-{HASH}, object-src none, base-uri none, frame-ancestors, Trusted Types, X-Content-Security-Policy obsolete, report-only vs enforced. NOT for general HTTP security headers (HSTS, COOP/COEP), Trusted Types deep dive, CORS configuration, or building a WAF.
tools
Choosing and operating an HTTP API versioning strategy that doesn't break clients — Stripe's date-based pinned versions, the Deprecation/Sunset header pair (RFC 9745 + RFC 8594), URI vs header vs media-type approaches, and the version-transformer pattern. Grounded in Stripe's published architecture and IETF RFCs.