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Agent Skill · 效率

youtube-cover-nano-banana(YouTube 封面纳米香蕉)

youtube-cover-nano-banana 用于处理图像、截图、视觉识别或图片素材相关工作,适合在 OpenClaw 中需要让 Agent 分析图片、整理视觉素材或辅助图像流程时使用。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。

youtube-cover-nano-banana 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在效率类的 21,003 个 Skill 里排第 7,198。

总安装 8,373周安装 356GitHub Stars 1下载 2,933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
MIT-0
版本
0.1.1

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:youtube-cover-nano-banana(YouTube 封面纳米香蕉)
来源仓库:https://github.com/luo-2q/youtube-cover-nano-banana
安装命令:
openclaw skills install youtube-cover-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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install youtube-cover-nano-banana

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

创建高转化率的 YouTube 缩略图概念、叠加文本、图像提示以及可选的 AI 生成的封面图像(来自原始标题、挂钩、脚本或素材)

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 OpenClaw;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 openclaw skills install youtube-cover-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

    它需要需要联网,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

youtube-cover-nano-banana 怎么安装?

在终端执行 openclaw skills install youtube-cover-nano-banana。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

youtube-cover-nano-banana 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

youtube-cover-nano-banana 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

youtube-cover-nano-banana 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

youtube-cover-nano-banana 用的人多吗?

公开数据是累计安装 8,373 次,近一周安装 356 次,下载 2,933 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。

youtube-cover-nano-banana 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
youtube-cover-nano-banana

YouTube 封面纳米香蕉 · 本页

8,3731需要联网MIT-0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

name
youtube-cover-nano-banana
description
Create high-converting YouTube thumbnail concepts, overlay text, image prompts, and optional AI-generated cover images from raw titles, hooks, scripts, or marketing copy. Use when Codex needs a YouTube thumbnail generator, YouTube cover image workflow, thumbnail prompt generator, or Nano Banana-based thumbnail creation skill.
version
0.1.1
metadata
{"openclaw":{"requires":{"env":["GEMINI_API_KEY","GOOGLE_API_KEY"],"bins":["python3"]},"primaryEnv":"GEMINI_API_KEY","emoji":"🖼️"}}

YouTube Cover Nano Banana

Overview

Analyze the user's text first. Then turn it into a thumbnail concept that is visually simple, emotionally obvious, and readable at small sizes.

Generate English image prompts for nano banana unless the user explicitly asks for another language. Keep reasoning grounded in YouTube thumbnail performance rather than generic poster design.

Use scripts/create_thumbnail.py for the full workflow when local script execution is available. It first calls Gemini text generation to turn source copy into a thumbnail plan, then optionally calls the official Gemini Nano Banana image endpoint. The scripts expect GEMINI_API_KEY or GOOGLE_API_KEY.

Workflow

1. Extract the message

Pull out:

  • Core topic
  • Intended audience
  • Main promise or tension
  • Emotional direction such as urgency, surprise, authority, fear, curiosity, or excitement
  • Best visual subject
  • Any non-negotiable details such as product, person, brand color, or forbidden elements

If the user only gives raw copy, infer the thumbnail angle from the strongest claim instead of mirroring the entire text.

2. Choose the thumbnail strategy

Prefer one dominant idea. Use one of these visual strategies:

  • Expressive face plus short text
  • Single object or product in dramatic close-up
  • Before versus after contrast
  • Threat, mistake, or warning framing
  • Curiosity gap with an incomplete reveal
  • Authority or proof framing with a clear focal object

Reject cluttered multi-idea compositions unless the user explicitly wants a collage.

3. Compress the on-image text

Write overlay text that is:

  • 2 to 6 words when possible
  • Readable in one second
  • Stronger than the original copy
  • Different from the full video title if needed

Do not place paragraphs, subtitles, or detailed bullet points inside the image prompt.

4. Build the nano banana prompt

Produce a prompt with these properties:

  • English language
  • 16:9 YouTube thumbnail composition
  • One dominant subject
  • Bold focal point
  • High contrast lighting and color separation
  • Clean background with supporting elements only
  • Space reserved for large headline text
  • Photorealistic or stylized only if the user requests it

Explicitly describe:

  • Subject appearance and pose
  • Camera framing
  • Emotion
  • Background environment
  • Color palette
  • Lighting
  • Text placement area
  • Thumbnail style cues such as cinematic, glossy, creator-economy, tech, finance, fitness, education

Use the template and examples in youtube-thumbnail-patterns.md when you need help selecting the structure.

5. Generate the image

Call nano banana with the final prompt after the concept is coherent.

For the full automated workflow, run:

python3 scripts/create_thumbnail.py \
  --copy "Man fights tiger" \
  --generate-image \
  --output-json "outputs/thumbnail-plan.json" \
  --image-output "outputs/generated-thumbnail.png"

This script:

  • Analyzes the source copy
  • Returns structured JSON with angle, overlay_text, prompt, and generation_notes
  • Optionally renders the image with Nano Banana
  • Writes a stable result envelope for integration use

If local script execution is available, run:

python3 scripts/generate_image.py \
  --prompt "<final english prompt>" \
  --angle "<angle>" \
  --overlay-text "<overlay text>" \
  --output "outputs/generated-thumbnail.png"

The script calls Gemini's official gemini-2.5-flash-image endpoint and saves:

  • The generated PNG
  • A sidecar JSON file with prompt, model, overlay text, and any text returned by the API

If tool calling or script execution is not available, still return the exact prompt plus a short note on what to generate.

6. Self-critique once

Before finalizing, check for the common failure modes:

  • Too many subjects
  • Text area too small
  • Weak contrast
  • Busy background
  • Vague emotion
  • No obvious click-driving angle
  • Prompt accidentally describes a poster instead of a thumbnail
  • Prompt includes tiny text or multiple lines of copy that image models render poorly

If a failure mode is present, revise the prompt once before returning it.

Output Format

Return four blocks in this order:

  1. Angle: one sentence describing the thumbnail idea
  2. Overlay Text: short text for the cover
  3. Nano Banana Prompt: the exact English prompt
  4. Generation Notes: one short sentence with any critical instruction or fallback

Constraints

  • Optimize for clickability and legibility on mobile.
  • Favor one subject over many.
  • Favor strong emotion over neutral expression.
  • Favor simple composition over descriptive completeness.
  • Do not invent celebrity likenesses, trademarks, or brand assets the user did not request.
  • Do not promise exact text rendering quality from the image model.
  • If the user supplies Chinese copy, analyze in Chinese if helpful but output the final image prompt in English.
  • If the user gives no style direction, default to modern YouTube thumbnail aesthetics with bold contrast and clean hierarchy.
  • If the user gives a niche that implies a visual style, reflect it in the prompt. Example: finance should feel sharp and credible; gaming can be more exaggerated; education should feel clear and authoritative.

Missing Information

Ask a brief follow-up only when a missing detail would materially change the output, such as:

  • Whether a specific person must appear
  • Whether a real product image is required
  • Whether the thumbnail should use photorealistic, 3D, illustrated, or anime style
  • Whether there are strict brand colors or banned visual elements

Otherwise, make reasonable assumptions and proceed.

Resources

scripts/

Use create_thumbnail.py for end-to-end copy-to-thumbnail generation.

Use generate_image.py to call Nano Banana directly and save output files.

references/

Use youtube-thumbnail-patterns.md for prompt scaffolds, angle selection rules, and example transformations from raw copy to thumbnail prompt.

Use publishing-contract.md as the integration contract for callers that need stable command behavior, output JSON, and exit codes.

平台分布

OpenClaw

97.68%
按下载量换算2,865

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

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