Nano Banana Image Skill

A production-grade, agent-portable image prompting skill for Nano Banana Pro and Nano Banana 2 / V2 in the Gemini image family. It turns fuzzy creative requests into clean interview questions, grounded art direction, model-aware prompt stacks, edit-preservation deltas, and structured JSON payloads.

The skill is built as an open Agent Skills package with a canonical SKILL.md entrypoint, plus companion files for agents that prefer AGENTS.md, CLAUDE.md, or GEMINI.md.

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What this skill is for

Use this repo when you want an agent to do any of the following well:

• write high-precision prompts for Gemini image generation,
• transform vague art direction into a complete production brief,
• preserve subject identity across edits and variants,
• create text-in-image layouts that do not collapse into typographic soup,
• route a request into the right style family, genre, movement, culture, capture mode, rendering pipeline, and output profile,
• package the final answer as structured JSON for downstream apps or API calls.

The skill is optimized for both speed workflows using Nano Banana 2 / V2 for fast iteration, and high-fidelity workflows using Nano Banana Pro for complex reasoning, stronger text rendering, and tighter instruction following.

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Companion package

This repository now includes a broader companion skill at packages/model-aware-image-prompt-engineer.

Use it when the target is not only Nano Banana. It routes image prompts across Gemini, OpenAI image models, Midjourney, FLUX, Qwen-Image, Z-Image, Stable Diffusion, Pony, Illustrious, NoobAI, Animagine, HunyuanImage, HiDream, OmniGen2, Sana, PixArt, Kolors, Chroma, Runway, Ideogram, Firefly, Recraft, Luma, local ComfyUI workflows, and hosted wrappers.

It also includes a public README hero and infographic:

• assets/hero.png
• assets/infographic.png

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Model targets

The skill keeps model choice explicit in both the human-readable brief and the runtime JSON.

Gemini API note: Google currently documents Gemini image generation through generateContent, with gemini-3-pro-image-preview for Nano Banana Pro, gemini-3.1-flash-image-preview for Nano Banana 2 / V2, and gemini-2.5-flash-image for the legacy fast path. Keep prompt text, image config, source references, and provenance notes separate in runtime payloads.

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Design goals

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Repository structure

nano-banana-image-skill/
├─ README.md
├─ SKILL.md                  # Canonical entrypoint (slim, under 500 chars)
├─ references/
│  └─ 00-orchestrator.md     # Full workflow (progressive disclosure)
├─ AGENTS.md                 # Codex / AGENTS-style context
├─ CLAUDE.md                 # Claude Code memory
├─ GEMINI.md                 # Gemini CLI memory
├─ agents/
│  └─ openai.yaml            # Codex UI metadata
├─ LICENSE                   # Apache-2.0
├─ .gitignore
├─ Makefile
├─ requirements-dev.txt
├─ schemas/
│  ├─ authoring-base.json    # Rich authoring contract
│  ├─ runtime-compact.json   # Compact runtime payload
│  └─ pack-format.json       # Pack manifest schema
├─ registry/
│  ├─ style-axes.md          # Style taxonomy
│  ├─ aliases.json           # Model and style aliases
│  ├─ forbidden-slop.json    # Slop scrubbing rules
│  ├─ interview-question-bank.json
│  └─ token-budgets.json
├─ skills/
│  ├─ core/                  # 20+ modular guidance files
│  ├─ families/              # Style family modules
│  ├─ genres/                # Genre modules
│  ├─ movements/             # Art movement modules
│  └─ ...                    # cultures, capture, pipelines, etc.
├─ examples/
│  ├─ authoring/             # 5 rich authoring briefs
│  └─ runtime/               # 5 matching runtime payloads
├─ scripts/
│  ├─ validate_repo.py       # Repository validator
│  ├─ compile_runtime.py     # Authoring-to-runtime compiler
│  └─ compile_gemini_request.py # Runtime-to-Gemini request skeleton
├─ docs/
│  ├─ index.html             # GitHub Pages landing page
│  └─ assets/                # Raster and SVG artwork (hero, infographic, flow, etc.)
└─ .github/workflows/
   └─ validate.yml           # CI validation workflow

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Compatibility strategy

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Quick start

Clone the repository

git clone https://github.com/Emily2040/nano-banana-image-skill.git
cd nano-banana-image-skill

Install as a skill

Codex / skill-aware clients:

mkdir -p ~/.agents/skills
ln -s /path/to/nano-banana-image-skill ~/.agents/skills/nano-banana-image-skill

Claude Code:

mkdir -p ~/.claude/skills
cp -R nano-banana-image-skill ~/.claude/skills/

Gemini CLI / Gemini Code Assist: Open the full repository as a workspace. Gemini reads GEMINI.md which imports the canonical SKILL.md.

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How the skill thinks

The high-level workflow is:

1. Interview the request and ask only the missing high-value questions.
2. Ground the scene, subject, era, materials, and real-world logic.
3. Route style, profile, platform, and overlays.
4. Bind references so identity and preserved elements do not drift.
5. Compile a clean prompt with explicit composition, lighting, and constraints.
6. Scrub slop and remove fashionable nonsense that wastes tokens.
7. Validate risk around ambiguity, policy, copyright, likeness, and text claims.
8. Emit schema output for both authoring and runtime.

The modular files under skills/core/ document each step in detail. The full orchestrator lives in references/00-orchestrator.md.

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Example scenarios

Five validated authoring + runtime example pairs live in examples/.

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Validation

Install dev dependencies

python -m pip install -r requirements-dev.txt

Run the repository validator

python scripts/validate_repo.py

Compile a runtime payload from an authoring brief

python scripts/compile_runtime.py examples/authoring/poster-edo-festival-text.json \
  -o /tmp/poster.runtime.json

Compile a Gemini request skeleton

python scripts/compile_gemini_request.py examples/runtime/poster-edo-festival-text.json \
  -o /tmp/poster.gemini-request.json

Make targets

make validate
make compile-examples

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GitHub Pages front-end

This repository includes a static landing page in docs/. To publish it:

1. Push the repo to GitHub.
2. Open Settings > Pages.
3. Choose Deploy from a branch.
4. Select the master branch and the /docs folder, or main if you rename the default branch.
5. Save.

A .nojekyll file is included to keep the static assets untouched.

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Author

Created by Iamemily2050

• GitHub
• Website
• X / Twitter
• Instagram

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License

Apache-2.0. See LICENSE.