sd2-pe

Generate Seedance 2.0 video prompts from ordered video and image references.

1.6k|121|Updated May 13, 2026
One-click install
npx skills add https://github.com/nolanx-ai/nolanx.ai --skill sd2-pe-nolanx-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sd2-pe
Source: https://github.com/nolanx-ai/nolanx.ai/tree/main/.nolanx/skills/sd2-pe
Command: npx skills add https://github.com/nolanx-ai/nolanx.ai --skill sd2-pe-nolanx-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It solves the challenge of turning ordered image/video references into Seedance 2.0 prompts that preserve continuity across time-sliced segments, reducing coherence breaks during video generation and extension.

Core Features & Use Cases

  • Ordered reference binding for multimodal inputs: Maps input videos/images to exact @video N and @image N labels so the model uses the intended visual timeline rather than guessing.
  • V2V extension continuity rules: Enforces that video-to-video prompts extend the previous tail (@video 1) without restarting action or reusing it as style-only reference.
  • Engineered 15-second prompt structure: Produces prompts with global lock, time-sliced storyboard, per-slice action/camera/performance/dialogue/sound, explicit continuity instruction, and quality/negative constraints.
  • Prompt review fallback checks: Strengthens missing or weak elements (asset mapping, continuity, contradictory camera moves, action timing, and quality constraints) instead of passing vague guidance onward.

Quick Start

Use sd2-pe when your workflow sends ordered @video and @image references for Seedance 2.0 generation or V2V extension to produce a coherent 15-second, continuity-enforced prompt set.

Frequently Asked Questions about sd2-pe

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

FAQPage Schema
How do I write Seedance 2.0 prompts that maintain visual continuity across video extensions?

To maintain Seedance 2.0 video continuity, structure prompts using strict @video N and @image N reference binding. This ensures the model uses the intended visual timeline rather than guessing, preventing coherence breaks during video generation and extension.

What is the best way to extend a video using video-to-video without restarting the action?

The best way to extend video-to-video without restarting action is to apply a V2V extension rule that explicitly extends the previous tail using @video 1. This prevents the model from treating the previous segment as a style-only reference.

How does time-sliced storyboard prompting work for 15-second video generation?

Time-sliced storyboard prompting works by dividing a 15-second video prompt into structured segments. Each slice contains specific action, camera, performance, dialogue, and sound instructions, bound to ordered @video and @image references for coherent generation.

Why do my image-to-video generations lose coherence when using multiple references?

Image-to-video generations lose coherence when missing or weak reference mappings cause the model to guess the visual timeline. Applying strict reference labeling and a pre-generation review fallback for missing mappings strengthens continuity.

Can I use multimodal inputs like images and videos together for Seedance 2.0 generation?

Yes, you can use multimodal inputs together by mapping input videos and images to exact @video N and @image N labels. This ordered reference binding ensures the model uses the intended visual timeline for coherent 15-second video generation.

What should a structured prompt layout include for continuity-enforced video generation?

A structured prompt layout for continuity-enforced video generation should include a global lock, time-sliced storyboard, per-slice action and camera instructions, explicit continuity instructions, and quality and negative constraints to ensure coherent output.