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banner-creatorbanner creator 搜索

Agent Skill

banner-creator 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

25,608

周安装

1,128

GitHub Stars

825

下载量

8,976
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

3

许可证

MIT

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:banner-creator(banner creator 搜索)
来源仓库:https://github.com/resciencelab/opc-skills
仓库路径:skills/banner-creator
安装命令:
npx skills add https://github.com/resciencelab/opc-skills --skill banner-creator
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/resciencelab/opc-skills --skill banner-creator

简介

通过迭代设计反馈和特定于平台的裁剪,创建由人工智能驱动的横幅。

  • 引导用户完成发现阶段,在生成之前收集需求(目的、目标比例、风格、内容元素、颜色)
  • 使用 nanobanana 技能以 21:9 的比例生成 20 个横幅变体,然后裁剪为目标格式(GitHub 为 2:1,Twitter 为 3:1,网站为 16:9)
  • 包括 HTML 预览模板,用于浏览变体并根据用户反馈进行迭代
  • 支持图像编辑以合并现有徽标和批量生成,并具有自动延迟以避免速率限制
  • 需要 Gemini API 密钥和 nanobanana 技能来生成 AI 图像

SKILL.md

Banner Creator Skill

Create professional banners through AI image generation with an iterative design process.

Prerequisites

Required API Keys (set in environment):

Required Skills:

  • nanobanana - AI image generation (Gemini 3 Pro Image)

File Output Location

All generated files should be saved to the .skill-archive directory:

.skill-archive/banner-creator/<yyyy-mm-dd-summaryname>/

Example:

.skill-archive/banner-creator/2026-01-19-opc-banner/
  banner-01.png
  banner-02.png
  ...
  banner-03-cropped.png
  preview.html

Workflow

Step 1: Discovery & Requirements

Before generating, gather requirements from user:

Ask about:

  1. Purpose - Where will the banner be used?

- GitHub README - Twitter/X header - LinkedIn banner - Website hero - YouTube channel art

  1. Target ratio/size - See references/formats.md:

- 2:1 (1280x640) - GitHub README - 3:1 (1500x500) - Twitter header - 16:9 (1920x1080) - Website hero

  1. Style preference:

- Match existing logo/brand? - Pixel art / 8-bit retro - Minimalist / flat design - Gradient / modern - Illustrated / artistic

  1. Content elements:

- Brand name / project name? - Tagline / slogan? - Logo character to include?

  1. Color preferences:

- Existing brand colors? - Let AI decide?

Wait for user confirmation before proceeding!

Step 2: Generate Banner Variations

Generate 20 banner variations using the nanobanana skill:

# Generate single banner
python3 <nanobanana_skill_dir>/scripts/generate.py "{style} banner for {brand}, {description}, {text elements}" \
  --ratio 21:9 -o .skill-archive/banner-creator/<date-name>/banner-01.png

# Batch generate 20 banners
python3 <nanobanana_skill_dir>/scripts/batch_generate.py "{style} banner for {brand}, {description}, {text elements}" \
  -n 20 --ratio 21:9 -d .skill-archive/banner-creator/<date-name> -p banner

Guidelines:

  • Generate at 21:9 ratio (widest available), crop later to target
  • Use batch_generate.py for multiple variations (includes auto-delay)
  • Use sequential naming: banner-01.png, banner-02.png, etc.

Image Editing (for incorporating existing logo):

python3 <nanobanana_skill_dir>/scripts/generate.py "add {logo character} to the left side of the banner" \
  -i /path/to/existing-logo.png --ratio 21:9 -o banner-with-logo.png

Step 3: Create HTML Preview

Copy the preview template and open in browser:

cp <skill_dir>/templates/preview.html .skill-archive/banner-creator/<yyyy-mm-dd-summaryname>/preview.html

Then open in default browser:

open .skill-archive/banner-creator/<yyyy-mm-dd-summaryname>/preview.html

IMPORTANT: Update the HTML to include the correct number of banners generated.

Step 4: Iterate with User

Ask user which banners they prefer:

  • "Which banners do you like? (e.g., #3, #7, #15)"
  • "What do you like about them?"
  • "Any changes you'd want?"

Based on feedback:

  1. Generate 10-20 more variations of favorite styles
  2. Use naming: banner-{original}-v{n}.png (e.g., banner-03-v1.png)
  3. Update HTML preview
  4. Repeat until user selects final banner

Step 5: Crop to Target Ratio

Once user approves a banner, crop to target size:

python3 <skill_dir>/scripts/crop_banner.py {input.png} {output.png} --ratio 2:1 --width 1280

Common targets:

  • GitHub README: --ratio 2:1 --width 1280 → 1280x640
  • Twitter header: --ratio 3:1 --width 1500 → 1500x500
  • Website hero: --ratio 16:9 --width 1920 → 1920x1080

Step 6: Deliver Final Assets

Present final deliverables:

## Final Banner Assets

| File | Description | Size |
|------|-------------|------|
| banner-03.png | Original (21:9) | 2016x864 |
| banner-03-cropped.png | GitHub README (2:1) | 1280x640 |

All files saved to: `.skill-archive/banner-creator/<yyyy-mm-dd-summaryname>/`
Copy final banner to user's desired location.

Quick Reference

Common Prompt Patterns

With Text:

Wide banner for {brand}, {style} style, featuring "{text}" prominently displayed, {colors}, {scene/elements}

With Character:

Wide banner featuring {character description}, {style} style, {scene}, text "{brand name}" on {position}, {colors}

Abstract/Gradient:

Abstract {style} banner, {colors} gradient, geometric patterns, modern tech feel, text "{brand}" centered

Scene-based:

{Style} illustration banner, {scene description}, {character} in {action}, "{brand}" text overlay, {colors}

Supported Aspect Ratios

Generate at widest ratio, then crop:

  • 21:9 - Ultra-wide (recommended for generation)
  • 16:9 - Wide
  • 3:2 - Standard wide

References

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

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

droid

30.23%
按下载量换算2,713

Claude Code

23.38%
按下载量换算2,099

Gemini CLI

19.88%
按下载量换算1,784

OpenCode

12.92%
按下载量换算1,160

Cursor

8.05%
按下载量换算723

Antigravity

3.45%
按下载量换算310

安全审计

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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。

来源信息

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