Seedance 视频生成

What This Skill Does

Seedance 视频生成 is a high-performance AI agent skill integrated with Bytedance's advanced Seedance model suite. It empowers OpenClaw users to generate professional-grade videos directly from text or existing images. This tool is uniquely capable of generating video content with synchronized audio—including dialogue, ambient sound effects, and background music—making it a game-changer for creators looking to produce cinematic content, commercials, or short dramas.

Installation

To integrate this skill into your environment, run the following command in your terminal: clawhub install openclaw/skills/skills/hexiaochun/seedance-video

Use Cases

This skill is versatile across multiple creative domains. Use it for:

1. Marketing and Advertising: Create high-definition promotional videos with AI-generated voiceovers and soundscapes.
2. Short-Form Content: Generate engaging clips for social media, including narrative-driven storytelling with character consistency.
3. Conceptual Prototyping: Visualize product designs or scenes using reference images to ensure consistent aesthetics.
4. Automated Film Production: Utilize the Pro 1.5 models for lip-sync and narrative dialogue to build complex character-driven scenes.

Example Prompts

1. "Generate a 5-second 1080p video of a futuristic cyberpunk city at night with neon lights reflecting in the rain, include atmospheric synth music."
2. "Use this image of a woman in a cafe as the first frame. Create a 7-second video of her smiling and taking a sip of coffee. Make sure the audio captures the ambient sound of the cafe."
3. "I need a professional video showcasing a brand new product based on these four reference images. Focus on cinematic camera pans and maintain strict visual consistency."

Tips & Limitations

• Cost Efficiency: Use generate_audio: false if you only need the visual component; this reduces the cost by half.
• Resolution: Choose 480p for quick iterations and previews, and scale to 1080p for final production to ensure maximum quality.
• Camera Control: Use the camera_fixed parameter to mimic tripod-style shooting, which is essential for stable product shots or static talking heads.
• Consistency: For the best results in maintaining character identity, rely on the lite/reference-to-video model, which is specifically optimized to respect 1-4 input reference frames. Note that video generation is computationally intensive; larger resolutions and longer durations will increase processing time and credit consumption.