Token导航 LogoToken导航

Agent Skill · 研究检索

nano-banana(Nano Banana 图像生成)

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。

nano-banana 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,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 31,945。

总安装 2,611周安装 111GitHub Stars 346下载 915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(Nano Banana 图像生成)
来源仓库:https://github.com/evoscientist/evoskills
仓库路径:skills/nano-banana
安装命令:
npx skills add https://github.com/evoscientist/evoskills --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/evoscientist/evoskills --skill nano-banana

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。

nano-banana 利用 Gemini 图像生成 API 制作高质量演示文稿图片,支持浏览器内交互式审阅与迭代编辑。适用于创建演讲幻灯片、讲座材料或论文插图等需要可视化表达内容的场景。可根据文档大纲自动生成视觉素材,并提供反馈驱动的精细化调整能力。

使用前需确认是否已授权访问目标页面或数据库,并区分读取与写入操作的权限边界。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/nano-banana

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/evoscientist/evoskills --skill nano-banana;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 怎么安装?

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

nano-banana 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 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 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 用的人多吗?

公开数据是累计安装 2,611 次,近一周安装 111 次,下载 915 次,GitHub 346 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 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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

Nano Banana 图像生成 · 本页

2,611346接触敏感数据未明确未通过

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

Generate high-quality presentation slides as images using Gemini's image generation API, review them interactively in a browser, and iteratively edit based on feedback.

When to Use This Skill

  • User asks to create a presentation, slide deck, or PPT
  • User wants to generate visual slides for a talk or lecture
  • User has a document or outline and wants slides based on it
  • User says "make me a PPT", "generate slides", "create a presentation"
  • User wants to edit or refine existing generated slides
  • User needs high-quality figures, diagrams, or illustrations for papers or documents
  • User asks to generate research figures, architecture diagrams, or concept illustrations

Do NOT use for:

  • Writing academic papers → use paper-writing
  • Planning academic conference talk narrative structure → use academic-slides

Before You Start: Prerequisites

Before proceeding with any slide generation, verify these prerequisites:

  1. API Key: Check that a Google API key is available. Run: echo $GOOGLE_API_KEY If empty, ask the user to provide one. They can either:

- Set it via config: EvoSci config set google_api_key <key> - Provide it directly (pass via --api-key argument) - If the user provides the key in conversation, pass it to scripts with --api-key

  1. Language: Ask the user what language the slide content should be in. This affects the content you write in slides_plan.json, not the style template.

Core Workflow

Phase 1: Content Planning Conversation     ← most important phase
Phase 2: Generate slides_plan.json
Phase 3: Select Style & Generate Slides
Phase 4: Launch Review Server
Phase 5: Apply Feedback Edits              ← repeat Phase 4-5 until satisfied
Phase 6: Package as PPTX
Phase 7: Cleanup

Follow these phases in order. Do NOT skip Phase 1 — the quality of generated slides depends directly on planning depth.


Phase 1: Content Planning Conversation

This is the most critical phase. Rushing to generation without proper planning produces mediocre slides. Engage the user in a structured conversation:

Step 1 — Understand the context:

  • What is the topic of the presentation?
  • Who is the audience? (technical peers, executives, students, general public)
  • How long is the talk? (this determines page count)
  • What is the occasion? (conference, internal talk, lecture, pitch)

Step 2 — Define the storyline:

  • What is the opening hook? (a surprising fact, a question, a trend)
  • What are the 3-5 main sections or arguments?
  • What is the key takeaway the audience should remember?
  • What is the closing message?

Step 3 — Outline per-page content:

  • For each slide, agree on: title + 2-4 key points + visual description
  • Identify which slides are cover, content, or data type
  • Ensure logical flow between pages

Duration-to-page-count guidance:

DurationPagesStructure
5 min5Cover + 3 content + closing
10-15 min8-12Cover + intro + 3-4 sections + summary + closing
20-30 min15-20Cover + intro + 5-6 sections + summary + closing
45-60 min25-30Cover + intro + 7-9 sections (2-3 pages each) + summary + closing

If the user provides a document or outline, read it thoroughly, then propose a slide breakdown for approval before proceeding.


Phase 2: Generate slides_plan.json

Create a slides_plan.json file in the workspace root with this schema:

{
  "title": "Presentation Title",
  "total_slides": 10,
  "slides": [
    {
      "slide_number": 1,
      "page_type": "cover",
      "content": "Title: My Presentation\nSubtitle: A subtitle here\nLabel: 2026 Edition"
    },
    {
      "slide_number": 2,
      "page_type": "content",
      "content": "Title: First Topic\nKey points:\n- Point one\n- Point two\n- Point three"
    },
    {
      "slide_number": 3,
      "page_type": "data",
      "content": "Title: Key Metrics\nMetric 1: 95% accuracy\nMetric 2: 3x faster\nMetric 3: 10k users"
    }
  ]
}

page_type values: cover, content, data

Critical Content Field Rules

The content field is what gets passed to the image generation model. Follow these rules strictly:

  1. DO write descriptive titles and bullet points
  2. DO describe the visual layout you want (e.g., "left-right comparison", "4 icon cards")
  3. DO NOT prefix lines with "Slogan:", "Visual:", "Points:", or any meta-labels — the model will render these as visible text on the slide
  4. DO NOT put the same sentence in both the title area and the bottom of the content — it causes duplication
  5. DO NOT include footer text, page numbers, or watermark instructions

Bad example (meta-labels leak as visible text):

Title: Why AI Matters
Visual: left-right comparison chart
Points:
- Point one
- Point two
Slogan: AI changes everything

Good example (clean, no meta-labels):

Title: Why AI Matters
Visual layout: left-right comparison chart showing traditional vs AI approach
Key points:
- Point one with brief explanation
- Point two with brief explanation
Bottom tagline: AI changes everything

Phase 3: Select Style & Generate Slides

Available Styles

StyleFileVisual CharacteristicsBest For
Lineal Colorstyles/lineal-color.mdWhite background, teal accents, flat 2D icons, info cardsTechnical talks, lectures, educational
Gradient Glassstyles/gradient-glass.mdLight pastel background, frosted glass cards, Apple Keynote feelProduct launches, pitches, SaaS
Vector Illustrationstyles/vector-illustration.mdCream background, black outlines, retro colors, toy-model charmEducational, children's content, brand stories

Present the styles to the user and let them choose. If unsure, recommend Lineal Color as the default.

Available Models

ModelSpeedQualityWhen to Use
gemini-3-pro-image-previewModerateBestFinal version, important presentations
gemini-3.1-flash-image-previewFastGoodDrafts, rapid iteration, large decks
gemini-2.5-flash-imageFastestBasicQuick prototypes, bulk generation

For first-time generation, recommend gemini-3.1-flash-image-preview (fast iteration). Switch to gemini-3-pro-image-preview for the final version.

Generate Command

python /skills/nano-banana/scripts/generate_ppt.py \
  --plan slides_plan.json \
  --style /skills/nano-banana/styles/lineal-color.md \
  --model gemini-3.1-flash-image-preview \
  --output ppt_output

Arguments:

  • --plan (required): Path to slides_plan.json
  • --style (required): Path to style template
  • --model: Image generation model (default: gemini-3-pro-image-preview)
  • --resolution: 2K (default) or 4K
  • --output: Output directory (default: ppt_output/TIMESTAMP)
  • --api-key: Google API key (if not in environment)
  • --workers: Number of parallel workers (default: 1, recommended: 3-5 for large decks)

Output structure:

ppt_output/
├── images/
│   ├── slide-01.png
│   ├── slide-02.png
│   └── ...
├── prompts.json    # All prompts used (for debugging)
└── index.html      # Browser viewer

Phase 4: Launch Review Server

Start the interactive review server so the user can review slides and write feedback:

python /skills/nano-banana/scripts/serve_viewer.py \
  --dir ppt_output \
  --plan slides_plan.json \
  --port 8080 \
  --pid-file .viewer.pid

Tell the user:

Review server is running at http://localhost:8080. Open it in your browser to review each slide. Write feedback in the text box below any slide that needs changes, then click "Save Feedback". Tell me when you're done.

The server saves feedback directly into slides_plan.json as a feedback field on each slide.

Wait for the user to confirm they have saved their feedback before proceeding.


Phase 5: Apply Feedback Edits

Read slides_plan.json and find all slides with a non-empty feedback field. For each one, run the edit script:

python /skills/nano-banana/scripts/edit_slide.py \
  --input ppt_output/images/slide-{NUMBER}.png \
  --instruction "{FEEDBACK_TEXT}" \
  --output ppt_output/images/slide-{NUMBER}.png \
  --model gemini-3.1-flash-image-preview

Arguments:

  • --input (required): Path to the original slide image
  • --instruction (required): The edit instruction (from feedback field)
  • --output: Output path (default: overwrite input)
  • --model: Image generation model
  • --api-key: Google API key (if not in environment)

After editing all slides with feedback, clear the feedback fields from slides_plan.json and tell the user to refresh the browser to see updated slides.

If the user has more feedback, repeat Phase 4-5. This review-edit cycle continues until the user is satisfied.


Phase 6: Package as PPTX

Once the user approves all slides, ask for the desired filename and package them:

python /skills/nano-banana/scripts/package_pptx.py \
  --dir ppt_output/images \
  --output presentation.pptx \
  --kill-server .viewer.pid

Arguments:

  • --dir (required): Directory containing slide-XX.png images
  • --output (required): Output.pptx file path
  • --kill-server: PID file from serve_viewer.py — automatically stops the review server after packaging

Phase 7: Cleanup

  • The review server is automatically stopped by package_pptx.py --kill-server
  • Ask the user if they want to keep ppt_output/ directory or clean it up
  • The slides_plan.json can be kept for future re-generation

Counterintuitive Rules

  1. Never include meta-labels in content — Words like "Slogan:", "Visual:", "Points:" will be rendered as visible text on the slide. Describe what you want without prefixes.
  2. Content describes WHAT, not HOW — The style template handles visual layout. The content field should focus on text and logical structure, not colors or positioning.
  3. More planning = better slides — Spending 10 minutes on Phase 1 conversation saves hours of re-generation. Do not rush to Phase 3.
  4. Edit, don't regenerate — When a slide needs minor changes (text fix, color change, remove footer), use edit_slide.py instead of regenerating from scratch. Editing preserves visual consistency.
  5. Use flash model for drafts — gemini-3.1-flash-image-preview is fast enough for iteration. Only switch to gemini-3-pro-image-preview for the final version after all feedback is addressed.
  6. Never read generated images yourself — Not all models support multimodal input. Do NOT use read_file on generated PNG images to check quality. Always launch the review server and let the user inspect slides visually in the browser. The user's feedback is your only quality signal.
  7. One idea per slide — Do not pack multiple concepts into a single slide. If a slide has more than 4 bullet points, split it into two slides.
  8. Bottom taglines should not repeat the title — If the title says "Why AI Matters", the bottom tagline should add new insight, not restate the title.

Scripts Reference

ScriptPurposeKey Arguments
scripts/generate_ppt.pyBatch generate all slides from plan--plan, --style, --model, --output, --resolution, --api-key, --workers
scripts/edit_slide.pyEdit a single slide based on instruction--input, --instruction, --output, --model, --api-key
scripts/serve_viewer.pyLocal review server with feedback--dir, --plan, --port, --no-open, --pid-file
scripts/package_pptx.pyPackage slide images into.pptx--dir, --output, --kill-server

Style Template Format

Style templates are markdown files in styles/ with a fixed structure that generate_ppt.py parses:

SectionPurposeParsed by Code
## Base PromptVisual specifications shared by all slidesYes — injected into every prompt
## Page TemplatesLayout descriptions per page typeFallback only
## ExamplesActual prompt templates with {Base Prompt} and [Content] placeholdersYes — primary templates
Other sectionsDocumentation onlyNo

To create a new style: copy an existing .md file, modify the ## Base Prompt and ## Examples sections. The code extracts ### Cover, ### Content, and ### Data code blocks from ## Examples.

平台分布

Codex

34.56%
按下载量换算316

Claude

30.08%
按下载量换算275

Cursor

18.49%
按下载量换算169

Gemini CLI

8.24%
按下载量换算75

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

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。

继续浏览同类 Skills