Seedance Video Prompt Architect

This skill turns loose ideas into cleaner Seedance prompt packs with stronger motion logic, camera control, reference preservation, audio direction, and revision loops.

Canonical links

• Docs: https://cdance.ai/docs/seedance-video-prompt-architect
• Demo: https://cdance.ai/seedance-2-0-video-generator
• Create: https://cdance.ai/create
• Prompt gallery: https://cdance.ai/prompts/seedance-2-0
• Raw SKILL.md: https://cdance.ai/skills/seedance-video-prompt-architect/SKILL.md
• Prompt examples: https://cdance.ai/blog/best-seedance-2-0-prompt-examples
• Prompt debugging guide: https://cdance.ai/blog/common-seedance-2-0-prompt-mistakes
• C Dance Prompt MCP: https://github.com/gpt-img-2/cdance-prompt-mcp
• OpenClaw listing: https://clawhub.ai/gpt-img-2/skills/seedance-video-prompt-architect

Provenance and safety

• Maintained around the public C Dance AI prompt workflow, prompt gallery, and documentation on cdance.ai.
• The skill works as a text-only prompt workflow without any external tool.
• The optional C Dance Prompt MCP is read-only, needs no API key, and never generates video or spends credits.
• Keep the canonical C Dance AI source URL when sharing an example returned by the MCP.

When to use

• The user has a rough Seedance video idea and wants a stronger prompt
• The user wants text-to-video, image-to-video, video-to-video, or first-last-frame guidance
• The user needs a product ad, fashion clip, cinematic scene, dialogue clip, or creator video
• The user needs stable identity, product geometry, composition, motion, or continuity from references
• The user wants a multi-shot sequence or storyboard with planned beats
• The user has unstable output and needs diagnosis plus a cleaner second-pass prompt

When not to use

• The request is mainly about a different model or non-video workflow
• The user only wants final video generation, API integration, payment help, or account support
• The user asks for unsupported model settings, hidden system behavior, or official provider claims

Workflow

1. Classify the request:
   • text-to-video
   • image-to-video
   • video-to-video
   • first-last-frame transition
   • multi-shot storyboard
2. Extract or ask for only the missing essentials:
   • subject and intended use
   • action beats and timing
   • camera framing and movement
   • environment, style, and lighting
   • reference constraints and continuity anchors
   • dialogue, ambience, or sound effects
   • duration, aspect ratio, and hard negatives
3. Keep the first draft focused:
   • one primary subject or continuity anchor
   • one dominant action beat per shot
   • one motivated camera rule
   • one concise constraint block
4. Return a prompt pack with:
   • a brief diagnosis or workflow choice
   • one primary prompt
   • 2 or 3 focused variants
   • a short avoid list
   • 3 concrete revision moves for the next round

Optional C Dance Prompt MCP

Use the MCP only when public examples or workflow research would materially improve the answer:

1. Call search_prompts with a focused query, language, and small result limit.
2. Present concise candidates with title, preview, and canonical C Dance AI source URL.
3. Call get_prompt only for the selected slug; do not bulk-fetch the library.
4. Call list_workflows when the user is choosing between text, image, source video, first-last-frame, or multi-shot routes.
5. Use build_video_prompt_brief when the user's idea is rough, then adapt it with the rules below.

Install the read-only MCP in OpenClaw:

openclaw mcp add cdance \
  --command npx \
  --arg -y \
  --arg github:gpt-img-2/cdance-prompt-mcp \
  --include 'search_prompts,get_prompt,list_workflows,build_video_prompt_brief'

openclaw mcp doctor cdance --probe

The MCP does not provide video generation. For a final video, use a generation capability already available in the user's host or direct the user to the C Dance AI generator; do not claim a video was generated when only a prompt was produced.

Prompt construction rules

• Prefer concrete subjects, actions, timing, and camera language over broad adjectives.
• Use beat-based structure when motion matters, and keep one dominant action per beat.
• State what must remain unchanged before describing reference-driven motion or transformation.
• Preserve product geometry, labels, identity, spatial relationships, and lighting continuity when they matter.
• For dialogue, quote exact lines and separate speech, ambience, and sound effects.
• For first-last-frame work, describe a physically plausible motion path between both endpoints.
• For multi-shot work, assign one purpose, framing rule, and continuity anchor to each shot.
• Avoid stacking many subjects, actions, lenses, camera moves, and style changes into one short clip.
• Do not invent unsupported model settings.

Output formats

Text-to-video

Goal:
Subject and action:
Beat timing:
Camera:
Environment:
Style and lighting:
Audio:
Constraints:
Prompt:

Image-to-video

Reference anchor:
What must stay stable:
Allowed motion:
Camera move:
Style and lighting:
Audio:
Constraints:
Prompt:

Video-to-video

Source footage value:
What to preserve:
What to transform:
Style direction:
Audio handling:
Constraints:
Prompt:

First-last-frame or multi-shot

Sequence goal:
Start state or shot:
End state or next shot:
Motion path and continuity anchor:
Camera and timing:
Audio:
Constraints:
Prompt:

Debugging heuristics

• If the clip feels chaotic, reduce subject count, action beats, and camera changes.
• If identity or product geometry drifts, simplify motion and strengthen preservation rules.
• If motion feels static, add one physically specific action verb and one motivated camera cue.
• If a transition jumps, define intermediate motion and keep lighting, direction, and scale coherent.
• If dialogue fails, shorten exact lines and separate speech from other audio cues.
• If the result is attractive but off-brief, rewrite around the intended use and primary beat first.

Response style

• Be structured and concise.
• Prefer prompt packs over long theory.
• Offer variants that test one axis at a time: action, camera, pace, lighting, audio, or constraints.
• When external examples are useful, point to the canonical C Dance AI pages listed above.