IMA AI Video Generator

What This Skill Does

IMA Studio Video Generation is a comprehensive, centralized AI video production hub within the OpenClaw ecosystem. It provides unified access to the industry's most powerful generative models, including Wan 2.6, Kling O1/2.6, IMA Video Pro, Google Veo 3.1, Sora 2 Pro, and Pixverse V5.5. Unlike fragmented approaches that require managing multiple API keys or platforms, this skill consolidates these models into a single, cohesive workflow. It handles various video generation modes such as text-to-video, image-to-video, first-frame conditioning, and reference-image-guided generation. By integrating with ima-knowledge-ai, it can maintain visual consistency across multi-shot projects, making it an ideal choice for professional content creation, character animation, and complex storytelling tasks.

Installation

To integrate this skill into your environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/allenfancy-gan/ima-video-ai

Use Cases

This skill is designed for high-level creative production. Use it for:

• Creating high-fidelity product demos with specific aesthetic constraints.
• Generating multi-shot narrative content where character consistency is critical.
• Producing professional-grade social media content using advanced models like Veo 3.1 or Kling O1.
• Developing explainer videos that require strict adherence to visual assets provided by the user.
• Bridging the gap between a single storyboard image and a fluid, animated sequence.

Example Prompts

1. "Generate a 10-second cinematic video of a futuristic car driving through a neon city at night, use Wan 2.6 for the generation."
2. "Take this reference image of a girl and animate her walking in a park, ensure she maintains the same clothes and hair throughout using Kling 2.6."
3. "Create a professional product video for my new luxury watch. The video should be 15 seconds long, use IMA Video Pro Fast for the animation, and focus on the metallic texture."

Tips & Limitations

• Model ID Accuracy: Always refer to the provided lookup table. Do not use informal names like "Kling" or "Wan" in the --model-id parameter; use the strict identifiers (e.g., kling-video-o1 or wan2.6-t2v).
• Mode Selection: Distinguish clearly between image_to_video (where the image is the source frame) and reference_image_to_video (where the image guides style). Incorrect selection will result in poor output quality.
• Consistency: When working on multi-shot videos, leverage the ima-knowledge-ai integration to ensure visual continuity. If the output varies, use the reference image mode to lock in character features.
• Performance: For quick iterations, prefer -fast variants like ima-pro-fast to optimize your workflow speed.