So I did, and now I have a cute little pelican on a bicycle bouncing around my desktop giving me updates on my Codex tasks.
The most interesting thing about this process was watching how the custom pet was created. I told it I wanted a custom pet that was a pelican riding a bicycle and GPT-5.6 Sol xhigh did the rest of the work, using several rounds with gpt-image-2 to generate the necessary sprite assets.
I had it make extensive notes and record all of the intermediary steps. My GItHub repo includes every generated image and combined sprite sheet, plus GIFs for each of the animation loops such as this one, called waving.gif:
That GIF was compiled from a single image generated by git-image-2
that looked like this:
And that image was created by executing this prompt against the initial generated character reference image, which was created with this prompt, which has this structure:
Create one clean full-body reference sprite for Codex pet Pedalican.
Pet identity: A compact adorable baby pelican with a round cream-white body, soft coral-orange bill and feet, riding a tiny sky-blue bicycle [...]
Place a single centered pose on a perfectly flat pure magenta #FF00FF chroma-key background. Keep the full pet visible, compact, readable at 192x208, and easy to animate. [...]
I've been looking out for example of ways to use image generation to create simple game-ready sprites, so I spent some time digging into this mechanism to see how it works.
The key implementation details are open source - these two skills in particular, both Apache 2.0 licensed:
And yes, GPT-5.6 Sol did come up with the name "Pedalican". I like it!
Tags: ai, prompt-engineering, generative-ai, llms, text-to-image, pelican-riding-a-bicycle, codex