video-generation

name	video-generation
description	Generate AI video with Veo or Sora. Triggers on text-to-video, image-to-video, video extension, style-consistent generation. Not for video analysis, research, or FFmpeg editing.

Video Generation

Generate AI video using Veo (MCP tools) or Sora (direct API script). This skill covers provider selection, generation modes, defaults, and the draft-to-final workflow.

For full tool references, model IDs, camera reliability data, and negative prompt blocks, see references/provider-details.md.

Provider Selection

Choose before writing prompts.

Need	Provider	Why
Native audio, 4K output, style/asset references, video extension	Veo	Veo 3.1 has the richer media-control surface
1080p production, text-heavy scenes, clean draft/final model split	Sora	sora-2 drafts + sora-2-pro finals is the most reliable loop
High-value hero shot, uncertain which provider wins	Both	Generate with both, pick winner from review evidence

Decision rules:

1. Veo when: native audio matters, you need 4K, you have style-anchor images for cross-clip consistency, or you need to extend an existing clip.
2. Sora when: 1080p is sufficient, the scene has on-screen text, or the draft-to-pro upgrade path saves iteration time.
3. Both when: the shot is expensive to reshoot and the extra cost of a bakeoff is justified.

Generation Modes

Text-to-Video

Prompt describes the scene. Both providers support this.

• Veo: mcp__veo__generate_video -- supports number_of_videos (1-4) for multi-take
• Sora: sora_direct.py create-and-poll -- single generation per call

Image-to-Video (I2V)

Animate a static image. Source image quality is critical.

• Veo: mcp__veo__animate_image -- absolute path to source image required
• Sora: sora_direct.py create-and-poll --input-reference -- auto-resizes/crops source to match output size

Video Extension

Continue an existing clip with new content.

• Veo: mcp__veo__extend_video_clip -- Veo 3.1 only, continues from last second
• Sora: sora_direct.py extend --id <video_id> -- extends by prompt

Styled Generation (Veo only)

Generate video with 1-3 reference images for visual consistency.

• mcp__veo__generate_video_with_style -- Veo 3.1 only
• Reference types: "asset" (preserves composition) or "style" (preserves palette/grain/lighting)

Default Settings

Veo Defaults

Parameter	Draft	Final
Model	veo-3.1-fast-generate-preview	veo-3.1-generate-preview
Resolution	720p	1080p
Duration	6s	8s
Aspect ratio	16:9	16:9
Negative prompt	Always include default block (see references)	Always include default block

Sora Defaults

Parameter	Draft	Final
Model	sora-2	sora-2-pro
Resolution	1280x720	1920x1080 (or 1080x1920 portrait)
Duration	4s	4s (or 8s for extended scenes)
Draft count	2	1

Draft-to-Final Workflow

Generate cheap drafts first, review, then produce the final with the quality model. This saves 60-70% on failed iterations.

Veo Path

1. Generate 2-3 variants with veo-3.1-fast-generate-preview at 720p
2. Review candidates (silence test at 1x, slow-motion scan at 0.5x)
3. Regenerate winner prompt with veo-3.1-generate-preview at 1080p

Sora Path (Preferred -- Automated)

1. Drafts: sora_direct.py production --stage drafts -- generates 2 clips with sora-2 at 720p
2. Review: sora_direct.py review-drafts -- Gemini scores each draft on 5 dimensions (prompt fidelity, temporal stability, surface realism, lighting coherence, text preservation)
3. Finalize: sora_direct.py finalize-from-review -- selects winner, launches sora-2-pro final at 1080p

All three steps require --run-dir with an absolute path. Relative paths break the review subprocess.

Camera Movement Reliability

Camera choice directly affects generation success rate. Summary:

Movement	Success Rate	Recommendation
Static	94-97%	Default for hero shots, UI demos
Zoom	81-87%	Good for reveals and emphasis
Pan	73-85%	Acceptable for environment shots
Tilt	67-81%	Use descriptive phrasing, not "tilt"
Tracking	58-68%	B-roll only, generate 3 variants
Crane	44-52%	Expect retakes
Combined	~29%	Never -- split into separate shots

For movements below 70%, always generate 3 variants. Full percentages and prompt phrasing in references/provider-details.md.

Key Constraints

Veo

• Always pass the negative prompt block (see references)
• All paths must be absolute
• extend_video_clip and generate_video_with_style require Veo 3.1
• Videos stay on Google servers for 2 days -- download promptly
• Named physical light sources required in every prompt (never "well-lit")

Sora

• OPENAI_API_KEY must be set
• --run-dir must be absolute for production workflows
• No real people, public figures, copyrighted characters
• Only non-human character uploads
• 720p drafts auto-map to compatible sizes when final target is 1080p
• I2V auto-resizes source images to match --size

Cost Reference

Provider	Model	Resolution	Duration	Cost
Veo	3.1 Standard	1080p	8s	~$3.20
Veo	3.1 Fast	720p	8s	~$1.20
Sora	sora-2	720p	4s	~$0.85
Sora	sora-2-pro	1080p	4s	~$3.50
Sora	sora-2-pro	1080p	8s	~$5.60

Typical scene (draft + final): $4-6 total.

Prompt Structure

Follow this template for both providers:

[Camera+Lens]: [Subject with physical detail] [Action with force verbs],
in [Setting with atmosphere], lit by [Named physical light source].
Style: [Texture micro-details, film grain]. Audio: [Ambient/SFX].

Rules:

1. Named physical light source -- always specify concrete light ("cool fluorescent overhead strips", not "well-lit")
2. Avoid dynamic physics -- no falling objects, fluids, collisions
3. Force-based verbs -- "grips handle and pulls" not "opens"
4. Micro-imperfections -- append "slightly grainy film-like quality, fine surface texture"
5. Exact descriptors -- copy-paste character/scene descriptions across shots, never paraphrase

Configuration

• Veo MCP server: veo in ~/.claude/.mcp.json
• Veo auth: GOOGLE_API_KEY or GEMINI_API_KEY
• Veo output: ~/Videos/veo-generated/
• Sora script: /Users/fausto_home/.claude/skills/sora/scripts/sora_direct.py
• Sora auth: OPENAI_API_KEY
• Run with: uv run --with requests python <script> <command> [args]

Related Skills

• video-production — multi-shot orchestration, chaining patterns, QA workflow
• image-generation — hero image generation for style anchors
• ffmpeg-production — post-processing, encoding, platform export