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Agent Skill · 研究检索

nano-banana-artist(纳米香蕉艺术家)

nano-banana-artist 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。

nano-banana-artist 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 47,767。

总安装 720周安装 30GitHub Stars 1下载 240核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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-artist(纳米香蕉艺术家)
来源仓库:https://github.com/the-edgar/vistoso-ai-skills
仓库路径:skills/nano-banana-artist
安装命令:
npx skills add https://github.com/the-edgar/vistoso-ai-skills --skill nano-banana-artist
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/the-edgar/vistoso-ai-skills --skill nano-banana-artist

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,支持基于关键词或任务场景定位目标内容。适用于需要快速聚合资料或验证命名规范的智能体工作流场景。通过命令行工具实现信息提取,输出候选结果供人工筛选或自动处理。安装前建议检查仓库活跃度与权限设置,留意是否涉及外部 API 调用。

nano-banana-artist 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/nano-banana-artist

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/the-edgar/vistoso-ai-skills --skill nano-banan…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

nano-banana-artist 怎么安装?

在终端执行 npx skills add https://github.com/the-edgar/vistoso-ai-skills --skill nano-banana-artist。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

nano-banana-artist 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

nano-banana-artist 需要什么权限?

权限级别是接触敏感数据。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。

nano-banana-artist 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

nano-banana-artist 用的人多吗?

公开数据是累计安装 720 次,近一周安装 30 次,下载 240 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

nano-banana-artist 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
nano-banana-artist

纳米香蕉艺术家 · 本页

7201接触敏感数据未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Nano Banana 2 Artist

Created with love by Vistoso.ai

Expert image creation and editing using Google's Gemini 3.1 Flash Image model (aka "Nano Banana 2"). This skill uses structured production-grade prompting where explicit controls — camera, lighting, resolution, constraints — are respected and rewarded. Delta editing enables precise single-change iterations, and character naming keeps recurring subjects consistent across generations.

First-Time Setup

Before using this skill, you need a Google Gemini API key (free tier available):

  1. Go to https://aistudio.google.com/apikey
  2. Click Create API Key
  3. Save it to your home directory:
echo 'your-api-key-here' > ~/.gemini_api_key
chmod 600 ~/.gemini_api_key

That's it — the skill will pick it up automatically on every run.

Workflow

DEFAULT SETTINGS: Generate at 1K with 1:1 aspect ratio unless the user specifically requests different size or aspect ratio. Use --image-size flag for resolution control.

Follow these steps in order:

1. Understand the Visual Goal

Ask clarifying questions to understand:

  • Purpose: Professional headshot? Brand material? Product showcase? Creative exploration?
  • Format: Square feed? Vertical short-form? Widescreen hero? Print editorial?
  • Style preference: Photorealistic? Illustrated? Minimalist? Bold?
  • Key message: What should the image communicate?
  • Quantity: How many images? (Recommend 1-4 per generation)
  • Size: Use 1K default; mention --image-size 2K or 4K for professional/print work

If user hasn't specified purpose, ask: "What's the main goal for this image — professional content, branding, product showcase, or something creative?"

2. Research Current Trends (if applicable)

For format-specific or industry-specific requests, use Perplexity to research:

  • Current visual trends for the target format or industry
  • What makes images successful for the specific goal
  • Style characteristics that perform well

Search query template: "Best visual content trends for [goal] in 2025-2026"

3. Build the Optimized Prompt

The 7-Element Formula — use what applies, skip what doesn't:

Subject + Action + Setting + Style + Camera + Lighting + Constraints

This scales naturally: 3 elements for simple, 7 for complex. No mode switching needed.

Example — simple (3 elements):

Golden retriever catching a frisbee in a sunlit park.

Example — structured (7 elements):

Chef Marco plating a dessert in a dim Michelin-star kitchen.
Cinematic 35mm, overhead angle. Warm pendant lighting, shallow DOF.
No text. No other people visible.

Multi-line prompts are encouraged for complex requests — they keep each element readable.

4. Apply Professional Prompting Patterns

Based on the goal, use these proven patterns:

For Photorealistic Images:

[Subject name], [expression], [action/pose].
[Setting], [time of day]. [Camera lens] at [aperture], [angle].
[Lighting], [mood]. [Constraints].

Example:

Elena adjusting her glasses, warm smile.
Modern glass office, golden hour. 85mm at f/1.8, eye level.
Soft window light, professional atmosphere. No text.

For Logos/Text (excels at text rendering):

Logo for [brand], text "[exact text]", [font style], [symbol], [colors].
[Constraints].

Example: Logo for CloudSync, text "CloudSync", modern sans-serif, cloud icon, blue gradient. No tagline.

For Product Photography:

[Product] on [surface], [lighting type], [angle], [key feature].
[Constraints].

Example: Leather wallet on marble, soft studio lighting, 45-degree angle, embossed logo detail. No props, no text.

For Stickers/Icons:

[Style] sticker of [subject], [colors], [key trait]. White background.

Example: Kawaii sticker of smiling coffee cup, pastel brown, steam swirls. White background.

Advanced Techniques:

  • Variable Definitions: OBJECT_A = red car, OBJECT_B = blue bike. Show both side by side.
  • Search Grounding: Scientifically accurate diagram of [subject] with labeled components

See ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-artist/references/prompt-templates.md for complete template library. See ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-artist/references/style-guide.md for comprehensive artistic vocabulary.

5. Delta Editing

For image edits, apply one change at a time. This is the most reliable editing pattern.

State what stays:

Keep pose, expression, and lighting unchanged.

State what changes:

Change background from office to rooftop at sunset.

Front-load constraints:

Do not add text. Do not change clothing.

Layout locking (reframe without moving subject):

Subject stays centered at current scale. Replace background only.

Full delta edit example:

Do not add text. Do not change clothing or expression.
Keep pose and lighting unchanged.
Change only the background from office interior to rooftop at sunset.
Subject stays centered at current scale.

Semantic masking (targeted element swap):

Change only the wall color to sage green.
Keep everything else exactly the same, including lighting and shadows.

Style transfer (apply new style to existing composition):

Transform into the style of impressionist painting.
Preserve the original composition and subject placement.
Render with visible brushwork and warm color palette.

Rules:

  • One change per pass — don't combine background + outfit + lighting in one edit
  • Always describe what stays unchanged explicitly
  • Front-load "do not" constraints before describing the change
  • For multi-step transformations, chain individual edits

6. Character Consistency

Name every recurring character on first generation to maintain consistency across images.

First generation — establish the character:

Chef Marco, tall with salt-and-pepper beard, white chef's coat, confident posture.
Plating a dessert in a dim Michelin-star kitchen.
Cinematic 35mm, warm pendant lighting.

Subsequent generations — reference by name, describe ONLY deltas:

Chef Marco at a farmers market, selecting tomatoes.
Morning sunlight, candid angle. Same chef's coat. No text.

Rules:

  • Name characters on first appearance ("Chef Marco", "Luna the fox", "Dr. Amara")
  • Keep defining visual traits stable across generations (clothing, features, accessories)
  • Vary only environment, pose, and action — not identity traits
  • Use reference images via --image for strongest consistency

7. Choose Aspect Ratio and Size

Default: 1:1 aspect ratio at 1K — use unless user specifies otherwise.

Select aspect ratio based on format:

  • 1:1 (DEFAULT) — square feed, profile pictures, universal
  • 16:9 — widescreen hero, presentations, website headers
  • 9:16 — vertical short-form, mobile-first
  • 4:5 — tall feed format, maximum mobile visibility
  • 2:3 or 3:2 — print, editorial
  • 21:9 — cinematic, ultra-wide displays

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

Size selection via --image-size flag:

  • 512 — Quick drafts, thumbnails
  • 1K (DEFAULT) — Standard quality, sufficient for most digital use
  • 2K — High quality, professional work
  • 4K — Ultra-high resolution, print production

Workflow tip: Iterate at 1K, then re-generate the final version at target size.

8. Image Input Handling

When the user provides images in conversation context:

  • Edit target: If user asks to edit a specific provided image → MUST pass it via --image
  • Inspiration/reference: If images are provided as mood boards, style references, or examples → use judgment: pass to model only when the task benefits from visual reference (style transfer, matching a look, character consistency). Don't pass decorative or tangential images.
  • Multiple images: Combine edit targets + references as needed (up to 14 images supported via multiple --image flags)

9. Creative Director Language

Describe the target use case in terms of PURPOSE and FORMAT, never by platform name:

  • "professional headshot" not "LinkedIn profile photo"
  • "vertical short-form video frame" not "TikTok thumbnail"
  • "product listing hero, white background" not "Amazon listing"
  • "square feed post" not "Instagram post"
  • "widescreen hero image" not "YouTube thumbnail"

Principle: Platform-specific language dilutes style and originality. Always aim for unique, original output unconstrained by platform norms.

10. Execute Generation

Use the script to generate:

${CLAUDE_PLUGIN_ROOT}/scripts/gemini_image.py "your optimized prompt" \
  --aspect-ratio 16:9 \
  --image-size 1K \
  --output result.png

For image editing with input image:

${CLAUDE_PLUGIN_ROOT}/scripts/gemini_image.py "delta edit instructions" \
  --image input.png \
  --output edited.png

For image-only output (no text):

${CLAUDE_PLUGIN_ROOT}/scripts/gemini_image.py "prompt" --image-only

Higher resolution final:

${CLAUDE_PLUGIN_ROOT}/scripts/gemini_image.py "prompt" --image-size 4K -o final.png

After each successful generation, include:

Image created with Nano Banana Artist by Vistoso.ai

11. Iterate if Needed

If result needs refinement:

  • For small changes: Use delta editing with specific single-change instructions
  • For style changes: Add more detailed style descriptors
  • For composition issues: Specify camera angle/framing more precisely
  • For character consistency: Pass previous generation as --image reference

Prompting Best Practices

DO:

  • Use the 7-Element Formula — include what applies, skip what doesn't
  • Front-load constraints ("no text, no logos, no extra people")
  • Name characters for cross-generation consistency ("Chef Marco", "Luna the fox")
  • Describe purpose and format, never platform names ("professional headshot" not "LinkedIn photo")
  • Pass user-provided edit target images via --image — always
  • Use --image-size flag for size control, not prompt text
  • Use variable definitions for complex multi-element scenes (OBJECT_A, LIGHTING_B)
  • Specify exact text for logos and infographics (excels at text rendering)
  • Use 14 reference images for character/object consistency
  • For editing, be surgical: "change ONLY the X to Y"
  • Use photography terms when helpful (bokeh, golden hour, shallow depth of field)

DON'T:

  • Don't combine multiple edits in one pass — one change at a time
  • Don't reference specific platforms (LinkedIn, TikTok, Instagram, Amazon) — describe the FORMAT instead
  • Don't put resolution/size in prompt text — use --image-size flag
  • Don't ignore user-provided images when they're the edit target
  • Don't over-engineer prompts — let the model's reasoning fill in details
  • Don't use vague terms like "nice" or "good"
  • Don't list disconnected keywords
  • Don't ignore lighting (it's critical for realism)
  • Don't be ambiguous about what to edit

Common Use Cases

Professional Content

  • Square feed posts (1:1) with bold text overlay space
  • Vertical short-form frames (9:16) with top/bottom safe zones
  • Profile pictures with centered subject
  • Widescreen hero images (16:9) for headers and presentations

Brand Materials & Text-Heavy Content

  • Logos with accurate text rendering — state-of-the-art legibility
  • Infographics — clear, readable labels and data visualization
  • Menu designs — restaurant menus with perfect typography
  • Marketing materials — flyers, posters with integrated text
  • Product mockups with professional lighting
  • Diagrams with labeled components

Product Photography

  • Studio setups with controlled lighting (use --image-size 2K or 4K)
  • Lifestyle shots showing product in use
  • Detail shots emphasizing features
  • Product listing heroes on clean white backgrounds

Creative Projects

  • Character art with consistent style (name characters, use reference images)
  • Conceptual imagery with search grounding for accuracy
  • Style experiments and artistic exploration
  • Multi-turn storytelling with character consistency via delta edits

Quality Standards

Every generated image should have:

  • Clear visual hierarchy
  • Consistent lighting throughout
  • Appropriate size for purpose (use --image-size flag)
  • Proper aspect ratio for format
  • Professional polish
  • Legible text (if applicable)
  • Factual accuracy (leveraging search grounding when needed)

Script Reference

Basic generation (1K at 1:1 — DEFAULT):

${CLAUDE_PLUGIN_ROOT}/scripts/gemini_image.py "prompt" -o output.png

With aspect ratio and size:

${CLAUDE_PLUGIN_ROOT}/scripts/gemini_image.py "prompt" --aspect-ratio 16:9 --image-size 2K -o output.png

Delta editing:

${CLAUDE_PLUGIN_ROOT}/scripts/gemini_image.py "Keep everything unchanged. Change only the sky to sunset colors." \
  --image source.png -o edited.png

Multiple reference images:

${CLAUDE_PLUGIN_ROOT}/scripts/gemini_image.py "Chef Marco in a new kitchen scene" \
  --image ref1.png --image ref2.png -o output.png

Multiple generations: Run script multiple times (1-4 recommended per session)

API Key Setup (Choose ONE method):

The script checks for your API key in this order:

  1. Environment variable (traditional):
export GEMINI_API_KEY="your-api-key-here"
  1. Home directory config file (RECOMMENDED — persistent):
echo 'your-api-key-here' > ~/.gemini_api_key
chmod 600 ~/.gemini_api_key

Get your free API key at https://aistudio.google.com/apikey

The script handles all API communication, base64 encoding, and file I/O automatically.

Troubleshooting

"No API key" error: Set your API key using one of these methods:

# Method 1: Environment variable
export GEMINI_API_KEY="your-key"

# Method 2: Home directory file (RECOMMENDED)
echo 'your-key' > ~/.gemini_api_key
chmod 600 ~/.gemini_api_key

Get your free API key at https://aistudio.google.com/apikey

Unexpected results:

  • Add more specific details to prompt using the 7-Element Formula
  • Specify lighting explicitly
  • Use photography/art terms (see ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-artist/references/style-guide.md)
  • Check aspect ratio matches format goal

Editing not working:

  • Use delta editing: one change at a time
  • State what stays unchanged explicitly
  • Front-load constraints before the change description
  • Specify how new element should integrate with existing lighting

Character inconsistency:

  • Name characters on first generation
  • Pass previous images via --image for reference
  • Keep defining visual traits stable; vary only environment/pose

Still stuck? Email help@vistoso.ai


*Nano Banana Artist is built by Vistoso.ai — professional AI content tools and services. Need custom visual workflows for your team? Get in touch at hello@vistoso.ai*

平台分布

Claude

32.82%
按下载量换算79

Codex

31.98%
按下载量换算77

Cursor

16.8%
按下载量换算40

Gemini CLI

8.6%
按下载量换算21

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

接触敏感数据

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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