Generate text-to-video content via the RunComfy CLI using the HappyHorse 1.0 endpoint.
npx skills add https://github.com/runcomfy-com/skills --skill happyhorse-1-0
Please help me install this Agent Skill. Skill: happyhorse-1-0 Source: https://github.com/runcomfy-com/skills/tree/main/happyhorse-1-0 Command: npx skills add https://github.com/runcomfy-com/skills --skill happyhorse-1-0
Generate high-quality text-to-video shots without manually dealing with model selection, routing, or endpoint details, while keeping audio and character consistency aligned to the same generation pass.
Use case: Create a short multilingual ad or a talking-head style explainer where the voiceover and ambient audio match the described scene flow.
Ask for a short, camera-directed, multi-shot video prompt and specify the desired aspect ratio and duration, then generate via the local RunComfy CLI for the HappyHorse 1.0 text-to-video endpoint.
High-intent search queries and answers about installing and using this skill.
To generate 1080p text-to-video with synchronized audio, provide a camera-directed, multi-shot prompt specifying aspect ratio and duration. The model routes requests to the HappyHorse 1.0 endpoint, producing video and matching ambient or dialogue audio in a single pass.
To maintain character consistency across multiple video shots, use anchor-based descriptions within your text-to-video prompt. This guides the model to keep character features aligned throughout storyboard-driven, camera-directed animation scenarios.
Yes, you can create multilingual video content with matching voiceover and ambient audio. The system generates synchronized audio during the same generation pass, ensuring dialogue and ambient sounds match the described scene flow.
Yes, you need the RunComfy CLI installed locally to run the text-to-video endpoint. The system invokes the CLI with a JSON prompt payload and returns downloaded result URLs from the CLI output directory.
For 1080p text-to-video workflows, you can configure aspect ratio, resolution, duration, seed, and watermark settings. These parameters are passed in the JSON prompt payload to control the final video output format.
A storyboard-driven approach for text-to-video generation helps structure prompts for multi-shot continuity. By using camera-directed anchor descriptions, you achieve better scene flow and visual consistency across generated 1080p video clips.
agentspace-soTranslate user prompts into HappyHorse 1.0 text-to-video API payloads for RunComfy.
MatrixReligioOrganize product video scenes into a confirmable storyboard sequence.
doany-aiGenerate text-to-video content with synchronized audio via RunComfy.
0xslineGenerate AI videos via Seedance 2.0, Kling, and MiniMax Hailuo models.
