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nano-bananaNano Banana 图像生成

Agent Skill

nano-banana 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

256

周安装

11

GitHub Stars

2

下载量

90
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:nano-banana(Nano Banana 图像生成)
来源仓库:https://github.com/devonjones/skill-nano-banana
仓库路径:skills/nano-banana
安装命令:
npx skills add https://github.com/devonjones/skill-nano-banana --skill nano-banana
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/devonjones/skill-nano-banana --skill nano-banana

简介

用于图像生成与编辑,基于 Google Gemini 3 Pro 模型实现文本到图像转换和多图合成。

  • 适合需要创意可视化、数据图表生成或快速原型设计的场景。
  • 通过 GitHub 安装,依赖 GEMINI_API_KEY 和特定 Python 包。
  • 使用前需设置环境变量并安装依赖,注意图像输出可能受模型限制影响。
  • 建议在非生产环境中先行验证提示词效果,避免生成不适宜内容。

SKILL.md

Nano Banana Pro

Image generation skill powered by Google's Gemini 3 Pro Image model. Enables text-to-image generation, image editing, multi-image composition, and real-time data visualization.

Requirements

  • GEMINI_API_KEY environment variable set
  • Python packages: google-genai, Pillow

Install dependencies:

pip install -r requirements.txt

Quick Start

Generate an Image

python scripts/generate_image.py "A cat wearing a wizard hat" cat.png

Edit an Existing Image

python scripts/edit_image.py photo.png "Add a sunset to the background" edited.png

Compose Multiple Images

python scripts/compose_images.py "Create a group photo in an office" team.png person1.png person2.png

Available Scripts

ScriptPurpose
generate_image.pyText-to-image generation
edit_image.pyEdit/modify existing images
compose_images.pyCombine up to 14 reference images
chat_image.pyInteractive multi-turn refinement
search_grounded_image.pyGenerate images with real-time search data

Generation Options

Aspect Ratios

1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9

Resolutions

1K (1024px), 2K, 4K

Usage with Options

python scripts/generate_image.py "Futuristic motorcycle on Mars" mars.png --aspect 16:9 --size 4K

Task Workflows

Logo Generation

python scripts/generate_image.py "Clean black-and-white logo with text 'Daily Grind', sans-serif font, coffee bean icon, minimalist style" logo.png --aspect 1:1

Product Mockup

python scripts/generate_image.py "Studio-lit product photo on polished concrete, 3-point softbox, 45-degree angle, professional e-commerce style" product.png --aspect 4:3 --size 4K

Photorealistic Portrait

python scripts/generate_image.py "A photorealistic close-up portrait, shot on 85mm lens, golden hour lighting, shallow depth of field, cinematic" portrait.png --size 4K

Stylized Art (Anime/Sticker)

python scripts/generate_image.py "A kawaii red panda sticker, bold outlines, cel-shading, white background, cute expression" sticker.png

Iterative Design Refinement

Use the chat script for back-and-forth refinement:

python scripts/chat_image.py

Then interact:

> Create a logo for 'Acme Corp'
[Image generated]
> Make the text bolder and add a blue gradient
[Refined image]
> save acme_logo.png

Real-Time Data Visualization

Generate infographics with current data:

python scripts/search_grounded_image.py "Visualize today's weather in Tokyo as an infographic" tokyo_weather.png --aspect 9:16

Use cases:

  • Live stock-market infographics
  • Breaking-news visuals
  • Weather dashboards
  • Current event visualizations

Multi-Image Composition

Combine reference images:

python scripts/compose_images.py "Create a product comparison shot with these items side by side, professional lighting" comparison.png item1.png item2.png item3.png --aspect 16:9

Use cases:

  • Product comparison shots
  • Character sheets
  • Team photos
  • Style-consistent image series

Inline Python Usage

For integration in larger scripts:

import os
from google import genai
from google.genai import types

client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])

response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents=["A serene mountain landscape at dawn"],
    config=types.GenerateContentConfig(
        response_modalities=['TEXT', 'IMAGE'],
        image_config=types.ImageConfig(
            aspect_ratio="16:9",
            image_size="2K"
        )
    )
)

for part in response.parts:
    if part.inline_data:
        image = part.as_image()
        image.save("landscape.png")

Editing with Inline Code

from PIL import Image
from google import genai
from google.genai import types

client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
img = Image.open("input.png")

response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents=["Add dramatic clouds to the sky", img],
    config=types.GenerateContentConfig(
        response_modalities=['TEXT', 'IMAGE']
    )
)

Prompting Tips

Photorealistic: Include camera settings, lighting, lens details

"Shot on 85mm lens, golden hour lighting, shallow depth of field"

Logos: Specify style, colors, typography

"Clean minimalist logo, sans-serif font, monochrome, vector style"

Product shots: Describe studio setup

"Studio-lit, 3-point softbox, polished surface, 45-degree angle"

Stylized art: Name the style explicitly

"Anime style, cel-shading, bold outlines, vibrant colors"

适合场景

01

文本生成图片

02

图片风格化

03

产品图和创意图

04

需要 FLUX 模型时

能力概览

能力 1

调用 FLUX 图像模型

能力 2

支持文本生图和图像改写

能力 3

覆盖 LoRA 或风格适配

能力 4

适合创意视觉生成

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.48%
按下载量换算30

Claude

31.39%
按下载量换算28

Cursor

17.49%
按下载量换算16

Gemini CLI

9.83%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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