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sd2-pe

Optimize Seedance 2.0 prompts for multimodal video generation.

Updated Apr 20, 2026
Search Tags:#workflow#multimodal#prompt-engineering#prompt-optimization#video-generation#ai-prompt#seedance
One-click install
npx skills add https://github.com/liudu2326526/comic-drama-platform --skill sd2-pe
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sd2-pe
Source: https://github.com/liudu2326526/comic-drama-platform/tree/main/docs/huoshan_api
Command: npx skills add https://github.com/liudu2326526/comic-drama-platform --skill sd2-pe

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The sd2-pe skill optimizes Seedance 2.0 prompts for multimodal video generation by converting rough prompts and assets into a structured, high-quality prompt framework.

Core Features & Use Cases

  • Applies the Seedance 2.0 prompt engineering framework to guide role, scene, and asset references for consistent video prompts.
  • Performs automatic asset mapping, multi-modal reference control, and stepwise prompt refinement to reduce ambiguity and improve render fidelity.
  • Suitable for initial prompts, media inputs, and prompt optimization tasks across end-to-end video generation workflows.

Quick Start

Provide your initial prompt and multimedia assets and I will transform them into a structured Seedance 2.0 prompt ready for generation.

Frequently Asked Questions about sd2-pe

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I optimize prompts for Seedance 2.0 multimodal video generation?▼

Seedance 2.0 prompt optimization converts rough prompts and multimedia assets into a structured framework using asset mapping, timeline control, and output quality constraints to improve video generation fidelity.

What is the best way to structure a multimodal video prompt using multimedia inputs?▼

A multimodal video prompt is structured by applying automatic asset mapping and multi-modal reference control, reducing ambiguity by defining roles, scenes, and asset references stepwise for consistent rendering.

Can I use this prompt engineering framework for initial prompts and prompt refinement tasks?▼

Yes, the prompt engineering framework applies to initial prompt creation, multimedia inputs, and prompt refinement tasks across end-to-end video generation workflows to guide structured output.

Do I need to provide multimedia assets for multimodal reference control to work?▼

Multimedia assets are required to perform automatic asset mapping and multi-modal reference control, transforming rough inputs into a high-quality prompt ready for video generation.

Why does my Seedance 2.0 video generation output have low render fidelity and high ambiguity?▼

Low render fidelity and ambiguity occur when prompts lack structured timeline control and asset mapping, which the Seedance 2.0 optimization framework resolves through stepwise prompt refinement.

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