Future Vision Custom Video Generation
Paste the following prompt into your AI chat to install this skill:
Please install @user_475a117f/future-vision-video-generation according to https://skillhub.cn/install/skillhub.md.
About this skill
Problem
Calling Future Vision video generation directly can hide operational details: missing auth, mismatched display names and stable enums, backend size validation, and tasks that are created before the video is finished. The skill focuses on direct custom video generation and keeps the workflow aligned with a shared CLI and a stable request contract.
How It Works
The skill first routes away from template remake, batch creative exploration, product TVC, and image-only output. It then calls the backend through a stable contract:
- Required parameters:
prompt;modelusesstandard,pro, orstable, with display names such as “Alibaba model” mapped topro;secondscommonly uses5,10, or15; andsizeis selected by model and validated by the backend. - Optional inputs:
resolution,referenceImage,referenceVideoUrls,referenceAudioUrls, andrequestKey. - Task state: it preserves reference media order, uses
x-idempotency-keyto avoid duplicate submissions from retries, and emits[SORA_TRACK]forqueued,pending, orrunningstates so downstream agents can keep polling.
Boundaries
A successful task creation does not mean the video is complete; work progress must be queried. When a required field is missing, ask for only one field at a time rather than asking for model, duration, and size together. If only a taskId is available, resolve it to a workId before polling. Authentication failures should be handled through the referenced docs, and the skill should not duplicate the full size/duration matrix.
Use Cases
- Submit a text prompt plus one reference image for image-to-video generation and track progress.
- Map Alibaba model to model=pro for a 10-second vertical video and choose a valid size.
- Use requestKey so network retries do not create duplicate video-generation tasks.
- Resolve taskId to workId before polling the video task status.
Best For
- Content engineers who submit product copy, reference images, or script prompts to a video-generation API.
- AI application engineers who orchestrate video task creation, parameter normalization, and status polling in agent workflows.
- Integration engineers who test model enums, size validation, and reference-media order for Future Vision.
- Frontend or backend engineers who need idempotent retries and task-tracking markers.
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