u/O-SideMedia

Hey everyone,

If you use Higgsfield AI for cinematic video/image generation, you already know the pain: the platform hosts 30+ models (Kling, Sora 2, Veo, Seedance, Wan, Hailuo, DoP, Soul, Nano Banana, Seedream, Flux, GPT Image…) and each one has its own quirks, named presets, and aspect-ratio rules. 

While working on our own projects and writing prompts, we wanted an easier and more consistent way to do it so I built one.

GitHub: https://github.com/OSideMedia/higgsfield-ai-prompt-skill

License: MIT

Its for Claude Co work or Claude Code and it does the prompt-construction work and turns your creative brief into a production-ready Higgsfield prompt using the MCSLA formula (Model · Camera · Subject · Look · Action), with the right model selected, named camera/motion presets verified against the platform, shared negative constraints appended, and aspect-ratio enums respected.

It isn't: another MCP wrapper. Higgsfield already ships official execution tooling. this is the  prompt layer that sits in front of it.

The split is intentional:

You can paste prompts straight into higgsfield.ai if you want. Or you can wire it up to any of Higgsfield's official MCP/CLI Tools

This skill → produces the prompt → Higgsfield's stack → executes it

Check it out and let me know what you think 😄

An AI short film inspired by Fast and Furious made entirely with Higgsfield AI and the Seedance 2.0 video model. Meet Kai, a street racer looking to make a name for himself in Vancouver's underground scene.

We wanted to push AI filmmaking beyond the typical robots and monsters you see everywhere. The goal was simple can these text to video tools actually tell a cinematic story with characters, tension, and stakes? VANCITY DRIFT is the result. A street racer named Kai challenges Lee, the reigning king of Vancouver's underground racing scene, and his crew. Every frame was generated using Higgsfield AI and the Seedance 2.0 model, then colour graded with Dehancer.