A cookbook for AI video pipelines, not a kitchen

What it does

This repository collects battle-tested workflows for a two-stage generative pipeline: GPT Image 2 generates consistent storyboards, character sheets, or product frames, then Seedance 2.0 animates them into video. The cases are scraped from X/Twitter creators and community experiments, organized by output type — commercials, music videos, game concepts, character animation, and production tooling.

The interesting bit

The real value isn’t the prompts themselves; it’s the composition strategies that reduce failure rates. The standout discovery is a 3×3 grid storyboard method: packing all panels into one image before feeding Seedance yields more coherent motion than sequential single-frame imports. Another pattern uses Claude Code to generate shotlists that then drive both image and video generation. These are operational hacks from people shipping content, not theoretical best practices.

Key highlights

• 30+ documented cases with before/after examples and attributed creator sources
• Covers niche pipelines: K-pop choreography grids, 3D-sculpt-to-AI-render-to-animation, casting-grid actor auditions
• Includes “storyboard-first cost control” — generating static frames before committing to expensive video generation
• Companion repos provide agent skills for Claude, Cursor, OpenCode, and OpenClaw integration
• Multi-language READMEs (10 languages) suggesting this is aimed at a global creator economy

Caveats

• Heavy Evolink branding and affiliate links throughout; the repository doubles as marketing funnel
• Most “cases” are descriptive blog-style walkthroughs, not reproducible code or configurations
• The “Quick Install” npx commands install Evolink’s proprietary skills, not open-source tooling

Verdict

Worth browsing if you’re already paying for GPT Image 2 and Seedance 2 and want to shortcut the experimentation phase. Skip it if you’re looking for self-hostable pipelines, API automation, or anything that works without Evolink’s services.