film-maker

Orchestrate film production stages from research through rendering and assembly.

1|Updated May 10, 2026
One-click install
npx skills add https://github.com/lostsock1/opencode-filmmaker --skill film-maker
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: film-maker
Source: https://github.com/lostsock1/opencode-filmmaker/tree/main/skills/brainstorming
Command: npx skills add https://github.com/lostsock1/opencode-filmmaker --skill film-maker

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires remotion, manim, sklearn, opencv-python, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the entire film-making process, from research to final assembly, ensuring every step is optimized and efficiently managed.

Core Features & Use Cases

  • Research and Development: Facilitate deep domain research and concept development.
  • Scene Table Creation: Automate the construction of structured scene tables.
  • AI-Driven Prompts: Generate AI-video prompts based on scene content.
  • Rendering: Execute deterministic Remotion/Manim renders for consistent visual output.
  • Quality Assurance: Perform comprehensive QA, review logs, and final assembly.
  • Use Case: For a director looking to create a short cinematic video, this skill will assist in developing the vision, scripting, visual design, reference extraction, prompt generation, and final renderings, all while ensuring a cohesive and polished final product.

Quick Start

To begin, invoke the film-maker skill with the command: film-maker --start <project-name>

Frequently Asked Questions about film-maker

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

FAQPage Schema
How do I automate the film-making pipeline from script to final video assembly?

Automating the film-making pipeline involves orchestrating research, script generation, scene table creation, AI prompt generation, and Remotion or Manim rendering into a structured sequence, ensuring every step is optimized and efficiently managed.

What is the best way to generate AI video prompts from a structured scene table?

Generating AI video prompts is handled by automating scene table construction and processing scene content directly through integrated AI logic, translating visual design and reference extraction into precise rendering instructions.

Do I need Python and Remotion installed to use AI-driven video production workflows?

Yes, you need Python libraries like OpenCV and Scikit-learn for script processing and AI integration, alongside Remotion and Manim installed in your environment to execute deterministic video renders and assembly.

Can Remotion and Manim be used together for deterministic video rendering?

Remotion and Manim can be used together within a structured pipeline to execute deterministic renders, ensuring consistent visual output for complex cinematic videos that combine code-driven animation and scene composition.

How does pipeline automation handle reference extraction for visual design in film production?

Pipeline automation handles reference extraction by processing domain research and scene content through Python libraries like OpenCV, structuring visual design data to generate precise AI-driven prompts for the rendering stage.