video-generation

Generate MP4 videos from structured JSON prompts via the Gemini API.

135|12|Updated Mar 30, 2026
One-click install
npx skills add https://github.com/Citrus-bit/medrix-flow --skill video-generation-citrus-bit
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: video-generation
Source: https://github.com/Citrus-bit/medrix-flow/tree/main/skills/public/video-generation
Command: npx skills add https://github.com/Citrus-bit/medrix-flow --skill video-generation-citrus-bit

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, and includes scripts (resource) components.

What problem does it solve?

This skill converts structured cinematic or storyboard-style prompts and optional reference images into runnable video generation jobs and final MP4 outputs, removing the need to manually craft API requests, manage uploads, or handle long-running polling and downloads.

Core Features & Use Cases

  • Structured JSON prompts capture title, scene description, characters, camera movement, dialogue and audio cues to produce consistent, reproducible generation inputs.
  • Reference image guidance accepts one or more images to define visual style or key frames and can act as a guided first/last frame.
  • Automated Python execution runs a provided script that calls the Gemini long-running video generation endpoint, polls for completion, and downloads the generated video into the outputs directory.
  • Use Case: Quickly prototype a short scene from a storyboard, create promotional clips from a narrative brief, or generate visual drafts for iterative creative review.

Quick Start

Generate a 16:9 short clip of a rainy city street at dusk by saving a structured JSON prompt to /mnt/user-data/workspace and running the skill to produce /mnt/user-data/outputs/rainy-street.mp4.

Frequently Asked Questions about video-generation

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

FAQPage Schema
How do I generate videos from structured prompts and reference images?

To generate videos from structured prompts, you provide a JSON file containing scene, camera, and audio specifications alongside optional reference images, and the Python script calls the Gemini API to output an MP4 file.

Can I use reference images to guide AI video generation?

You can use reference images to guide AI video generation by providing image paths that define visual style or act as guided first and last frames for the Gemini API request.

Do I need a Gemini API key to run the video generation script?

You need a GEMINI_API_KEY environment variable configured to execute the Python script, as it authenticates requests to the Gemini long-running video generation endpoint.

What is the best way to automate storyboard to video prototyping?

The best way to automate storyboard to video prototyping is structuring scene descriptions, characters, and camera movements into a JSON prompt, which the Python script processes into a reproducible MP4 output.

How does the Python script handle long-running video generation API calls?

The Python script handles long-running video generation by calling the Gemini endpoint, automatically polling for completion status, and downloading the final generated video into the outputs directory.

What limitations exist when generating short clips from JSON prompts?

Limitations of generating short clips from JSON prompts include dependency on the requests library and the Gemini API, requiring structured JSON inputs for consistent results rather than free-form text descriptions.