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When the user wants to create, generate, or produce video content using AI tools or programmatic frameworks. Also use when the user mentions 'video production,' 'AI video,' 'Remotion,' 'Hyperframes,' 'HeyGen,' 'Synthesia,' 'Veo,' 'Sora,' 'Runway,' 'Kling,' 'Seedance,' 'Hailuo,' 'MiniMax,' 'Pika,' 'Hunyuan,' 'Wan,' 'video generation,' 'AI avatar,' 'talking head video,' 'programmatic video,' 'video template,' 'explainer video,' 'product demo video,' 'video pipeline,' 'copy this edit,' 'match this video style,' 'reverse-engineer this video,' 'edit like this reference,' or 'make me a video.' Use this for video creation, generation, and production workflows. For video content strategy and what to post, see social. For paid video ad creative, see ad-creative.

Use this Skill: https://skilld.dev/gh/coreyhaines31/marketingskills/video

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referencesai-video-prompting.md

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AI Video Prompting Guide

How to write effective prompts for AI video generation models (Veo, Runway, Kling, Pika).


Prompt Structure

A strong video prompt follows this formula:

[Subject] + [Action] + [Camera movement] + [Visual style] + [Lighting/mood] + [Technical specs]

Example Prompts by Use Case

Product hero shot:

A sleek laptop on a minimal white desk, screen glowing with a dashboard UI,
camera slowly orbits 180 degrees around the desk,
soft volumetric lighting from the left, shallow depth of field,
cinematic commercial aesthetic, 4K

Lifestyle B-roll:

A woman in a modern co-working space smiling while looking at her phone,
natural window light, candid documentary feel,
camera handheld with subtle movement, warm color grading

Abstract/brand:

Flowing liquid gold particles forming the shape of a network graph,
dark background, particles catch light as they move,
slow-motion macro photography style, dramatic rim lighting

SaaS explainer scene:

An overhead shot of a team around a conference table pointing at charts,
camera slowly pushes in, bright modern office,
clean corporate style, even lighting, 1080p

Camera Movement Vocabulary

Use these terms — video models understand them:

Term Effect
Static Locked camera, no movement
Pan left/right Camera rotates horizontally
Tilt up/down Camera rotates vertically
Dolly in/out Camera moves toward/away from subject
Orbit Camera circles around subject
Tracking shot Camera follows moving subject
Crane/aerial Camera rises or descends
Handheld Subtle shake, documentary feel
Zoom Lens zoom (different from dolly)
Slow push Gradual dolly in — builds tension/focus

Style Keywords

Cinematic

  • "cinematic color grading"
  • "anamorphic lens flare"
  • "shallow depth of field"
  • "film grain"
  • "35mm film"

Commercial/Corporate

  • "clean commercial lighting"
  • "bright and airy"
  • "professional corporate aesthetic"
  • "even, diffused lighting"

Documentary

  • "handheld documentary style"
  • "natural lighting"
  • "candid, unposed"
  • "observational camera"

Social/Trendy

  • "vertical 9:16"
  • "fast-paced cuts"
  • "bold text overlays"
  • "high contrast, saturated colors"

Model-Specific Tips

Veo (Google)

  • Excels at photorealism and complex scenes
  • Supports audio generation synced to video
  • Best with detailed, descriptive prompts
  • Specify "high resolution" or "1080p" for best quality
  • Can handle multiple subjects and scene transitions

Runway Gen-4

  • Strong motion control — specify camera movements precisely
  • Best temporal consistency (subjects stay consistent across frames)
  • Use motion brush for specific area animation
  • Image-to-video works well — provide a reference frame
  • Keep prompts under 100 words for best results

Kling

  • Can generate up to 2 minutes (much longer than others)
  • Good for longer narrative sequences
  • More affordable for bulk generation
  • Quality drops slightly at longer durations
  • Best with simpler scenes and fewer subjects

Pika

  • Fastest generation time (under 2 minutes)
  • Good for quick iterations and experimentation
  • Effects mode adds motion to still images
  • Best for short clips (5-15 seconds)
  • Less control over camera movement

Common Prompt Mistakes

Mistake Why It Fails Fix
"A person using our app" Too vague, no visual detail Describe the person, setting, lighting, camera
Including text/logos AI can't render readable text Add text in post via Hyperframes/CapCut
"Make it viral" Not a visual instruction Describe the visual style you want
Extremely long prompts (200+ words) Models lose focus Keep to 50-100 words, be specific
No camera direction Random/static camera Always specify movement or "static"
"Realistic" alone Not specific enough "Photorealistic, natural lighting, shot on RED camera"

Prompting Workflow

  1. Reference first — find a real video that looks like what you want
  2. Describe it — break down: subject, action, camera, style, mood
  3. Generate 3-4 variations — same concept, different angles or styles
  4. Iterate on the best — refine the prompt based on results
  5. Composite — combine AI footage with programmatic text/overlays

Aspect Ratios

Always specify in your prompt or generation settings:

Platform Ratio Resolution
YouTube 16:9 1920x1080 or 3840x2160
TikTok/Reels/Shorts 9:16 1080x1920
Instagram Feed 1:1 or 4:5 1080x1080 or 1080x1350
Website hero 16:9 1920x1080
LinkedIn 16:9 or 1:1 1920x1080

Cost Optimization

  • Iterate at low resolution — upscale only the final version
  • Use Kling for drafts — cheapest per second, switch to Veo/Runway for finals
  • Image-to-video — providing a reference frame saves generation credits and gives better results
  • Batch similar prompts — models often offer volume discounts
  • Cache and reuse — B-roll clips can be reused across multiple videos

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub16d

    The skill is safe for its intended use but contains an indirect prompt injection surface as it is designed to ingest and analyze external video content and social media metadata.

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    Risk: MEDIUM · 1 issue

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metadata
{
  "version": "2.1.0"
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