dharani2201-mini/nano-banana-prompting — explained in plain English
Analysis updated 2026-05-18
Keep a character's face and appearance consistent across many AI image generations.
Reduce the plastic, overly smooth look common in AI-generated portraits.
Generate a consistent still image to use as a reference for video generation tools.
Copy a ready-made JSON template as a starting point for a new character or scene prompt.
| dharani2201-mini/nano-banana-prompting | 0xkinno/neuralvault | 0xmayurrr/ai-contractauditor | |
|---|---|---|---|
| Stars | 1 | 1 | 1 |
| Language | — | TypeScript | TypeScript |
| Setup difficulty | easy | hard | easy |
| Complexity | 1/5 | 4/5 | 2/5 |
| Audience | vibe coder | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Just JSON templates to copy and edit, requires access to Nano Banana or a similar image generation model to use them.
Nano Banana Prompting is a collection of JSON prompt templates for Nano Banana, Google's Gemini based image generation model, and other structured image generators. It is not code you install and run, it is a set of prompt patterns and guides meant to solve two common problems people run into with AI generated images: the same character's face changing between different generations, and images having a plastic, overly smoothed, obviously AI-made look. The repository is organized into a few folders. A SKILL.md file explains the full method and is written so it also works as a Claude Code skill. An examples folder has several complete, ready to copy prompts, including a before and after comparison showing a normal prompt next to one built with this project's approach. A templates folder has starter JSON files with placeholders a user fills in for their own character or scene, and a guides folder explains the two main techniques in more detail. The first technique is an identity_lock block inside the JSON prompt, which describes a character's specific features, such as hair, skin, and any small distinguishing details, along with a list of things to preserve and a list of rules like no face swap or no beautify. The idea is that vague descriptions produce a different looking person every time, while specific, repeated details keep the same character recognizable across many generations. The second technique combines positive realism_rules describing imperfections a real photo would have, such as visible skin texture or harsh sunlight, with a negative_prompt list explicitly banning things like porcelain skin or a beauty filter look. The README notes that this format is for still images only, and suggests generating a still first, then feeding it into a video model like Veo 3, Sora, or Kling as a reference image, since those tools tend to work better with prose prompts rather than JSON. The project can also be installed directly as a Claude Code skill by cloning it into the user's skills folder. It is released under the MIT license.
A collection of JSON prompt templates and techniques for keeping AI-generated character images consistent and photorealistic in Nano Banana.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly vibe coder.
This repo across BitVibe Labs
Verify against the repo before relying on details.