nanobanana

nanobanana is a skill for Claude Code from ReScienceLab/opc-skills. It costs 65 tokens per session (1,352 once invoked), scanned A, original, Apache-2.0.

An image-generation and image-editing skill using Google's Gemini 3 Pro Image model, also called Nano Banana Pro.

In plain words
What is it for?
Use it to create images, edit a supplied image, select an aspect ratio, or request a 2K or 4K result.
Why use it?
It provides a documented way to turn text prompts into images or change existing images, including choosing proportions and output size.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the nanobanana plugin — 1 skill shipped together

Good fit Use it to create images, edit a supplied image, select an aspect ratio, or request a 2K or 4K result.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/resciencelab/opc-skills/nanobanana
About the project

OPC Skills is a collection of reusable instruction folders, scripts, and resources that extend coding agents with specialized tasks for solopreneurs and one-person companies. Its skills cover areas such as search optimization, demand research, domain discovery, branding, social-media assets, and platform-specific research. The catalogue entries are the project's own skills, plugins, and hook.

ReScienceLab/opc-skills · 1,768 stars · on GitHub · opc.dev

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ReScienceLab/opc-skills --skill nanobanana
Clone the repo
git clone --depth 1 https://github.com/ReScienceLab/opc-skills

Made for: Claude Code.

Or install nanobanana, the plugin that ships this one along with the rest of its 1 skill.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for nanobanana

README.md
[![agentmods](https://agentmods.dev/badge/skills/resciencelab/opc-skills/nanobanana/github.svg)](https://agentmods.dev/skills/resciencelab/opc-skills/nanobanana)
Your own site
<a href="https://agentmods.dev/skills/resciencelab/opc-skills/nanobanana"><img src="https://agentmods.dev/badge/skills/resciencelab/opc-skills/nanobanana/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for nanobanana

Your own site · 80×15
<a href="https://agentmods.dev/skills/resciencelab/opc-skills/nanobanana"><img src="https://agentmods.dev/badge/skills/resciencelab/opc-skills/nanobanana.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,352 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 18 Mar 2026
  • Snyk pass 17 Feb 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00065 $0.01352
Opus 5 $0.00032 $0.00676
Sonnet 5 $0.00013 $0.00270
Haiku 4.5 $0.00006 $0.00135

Measured 10d ago against content hash 908d7922615b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

nanobanana scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/batch_generate.py, scripts/generate.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/nanobanana/SKILL.md · 202 lines

How it starts

The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Nano Banana - AI Image Generation

Generate and edit images using Google's Gemini 3 Pro Image model (gemini-3-pro-image-preview, nicknamed "Nano Banana Pro" 🍌).

Prerequisites

Required:

  • GEMINI_API_KEY - Get from Google AI Studio
  • Python 3.10+ with google-genai package

Install dependencies:

pip install google-genai pillow

Quick Start

Generate an image:

python3 <skill_dir>/scripts/generate.py "a cute robot mascot, pixel art style" -o robot.png

Edit an existing image:

python3 <skill_dir>/scripts/generate.py "make the background blue" -i input.jpg -o output.png

Generate with specific aspect ratio:

python3 <skill_dir>/scripts/generate.py "cinematic landscape" --ratio 21:9 -o landscape.png

Generate high-resolution 4K image:

python3 <skill_dir>/scripts/generate.py "professional product photo" --size 4K -o product.png

Script Reference

scripts/generate.py

Main image generation script.

Usage: generate.py [OPTIONS] PROMPT

Arguments:
  PROMPT              Text prompt for image generation

Options:
  -o, --output PATH   Output file path (default: auto-generated)
  -i, --input PATH    Input image for editing (optional)
  -r, --ratio RATIO   Aspect ratio (1:1, 16:9, 9:16, 21:9, etc.)
  -s, --size SIZE     Image size: 2K or 4K (default: standard)
  --search            Enable Google Search grounding for accuracy
  -v, --verbose       Show detailed output

Supported aspect ratios:

  • 1:1 - Square (default)
  • 2:3, 3:2 - Portrait/Landscape
  • 3:4, 4:3 - Standard
  • 4:5, 5:4 - Photo
  • 9:16, 16:9 - Widescreen
  • 21:9 - Ultra-wide/Cinematic

scripts/batch_generate.py

Generate multiple images with sequential naming.

Usage: batch_generate.py [OPTIONS] PROMPT

Arguments:
  PROMPT              Text prompt for image generation

Options:
  -n, --count N       Number of images to generate (default: 10)
  -d, --dir PATH      Output directory
  -p, --prefix STR    Filename prefix (default: "image")
  -r, --ratio RATIO   Aspect ratio
  -s, --size SIZE     Image size (2K/4K)
  --delay SECONDS     Delay between generations (default: 3)

Read the full file on GitHub · 202 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 202 lines · 65 tokens per session scan A 908d7922615b

Subscribe to this mod's changes

nanobanana is a skill published in the GitHub repository ReScienceLab/opc-skills (1,768 stars, last pushed yesterday), licensed Apache-2.0. It adds 65 tokens to every session and 1,352 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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