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Agent Skill · 图像处理

cover-image(封面图片)

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制;涉及人物、品牌、商品或公开展示素材时,应额外核对授权、真实性和内容合规边界。

cover-image 是图像处理类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证为 MIT,暂无第三方扫描结果,按安装量在图像处理类的 1,562 个 Skill 里排第 1,254。

总安装 636周安装 26GitHub Stars 公开资料未说明下载 204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

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:cover-image(封面图片)
来源仓库:https://github.com/zlh-428/naruto-skills
仓库路径:skills/cover-image
安装命令:
npx skills add zlh-428/naruto-skills --skill "cover-image"
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。

AgentSkills.tonpx skills
npx skills add zlh-428/naruto-skills --skill "cover-image"

这个 Skill 是做什么的

图像处理类 Skill 处理生成、裁剪、压缩和批量转换图片的任务。

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。适合让 Agent 根据文本生成图片、处理背景或调用相关图像工具。通过 github 安装,支持 Codex、Claude、Cursor、Gemini CLI 宿主环境。使用时需确认输入图片、版权来源、输出格式和模型限制,涉及人物或品牌时应核对授权。

具体用法请结合来源仓库和原始 README 文档进一步核验。

来源仓库内路径:skills/cover-image

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 zlh-428/naruto-skills --skill "cover-image";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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

cover-image 怎么安装?

在终端执行 npx skills add zlh-428/naruto-skills --skill "cover-image"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

cover-image 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。

cover-image 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

cover-image 是免费的吗?

来源标注的许可证是 MIT。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。

cover-image 用的人多吗?

公开数据是累计安装 636 次,近一周安装 26 次,下载 204 次。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。

cover-image 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

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。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 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。
  • 需要处理图像处理类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

图像处理类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
ai-image-generation

AI 图像生成 · Codex、Claude

4,365,552382调用外部服务未明确有提醒
openai-image-gen

OpenAI 图像生成 · OpenClaw

1,906,88432需要联网MIT-0有提醒
image

图像 · OpenClaw

525,99926需要联网MIT-0通过
baoyu-cover-image

宝玉封面图 · Codex、Claude

474,24016,779只读MIT有提醒
baoyu-image-gen

宝玉图像生成器 · Codex、Claude

468,00716,778接触敏感数据MIT通过
cover-image

封面图片 · 本页

636—只读MIT未收录

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
cover-image
description
Generate elegant cover images for articles. Analyzes content and creates eye-catching hand-drawn style cover images with multiple style options. Use when user asks to "generate cover image", "create article cover", or "make a cover for article".

Cover Image Generator

Generate hand-drawn style cover images for articles with multiple style options.

Usage

# From markdown file (auto-select style based on content)
/cover-image path/to/article.md

# Specify a style
/cover-image path/to/article.md --style blueprint
/cover-image path/to/article.md --style warm
/cover-image path/to/article.md --style dark-atmospheric

# Without title text
/cover-image path/to/article.md --no-title

# Combine options
/cover-image path/to/article.md --style minimal --no-title

# From direct text input
/cover-image
[paste content or describe topic]

# Direct input with style
/cover-image --style playful
[paste content]

Options

OptionDescription
--style <name>Specify cover style (see Style Gallery below)
--aspect <ratio>Aspect ratio: 2.35:1 (cinematic, default), 16:9 (widescreen), 1:1 (social)
--lang <code>Output language for title text (en, zh, ja, etc.)
--no-titleGenerate cover without title text (visual only)

Style Gallery

StyleDescription
elegant (Default)Refined, sophisticated, understated
flat-doodleBold outlines, pastel colors, cute rounded shapes
blueprintTechnical schematics, engineering precision
bold-editorialMagazine cover impact, dramatic typography
chalkboardBlack chalkboard, colorful chalk drawings
dark-atmosphericCinematic dark mode, glowing accents
editorial-infographicMagazine explainer, visual storytelling
fantasy-animationGhibli/Disney inspired, whimsical charm
intuition-machineTechnical briefing, bilingual labels
minimalUltra-clean, zen-like, focused
natureOrganic, calm, earthy
notionClean SaaS dashboard, productivity styling
pixel-artRetro 8-bit, nostalgic gaming aesthetic
playfulFun, creative, whimsical
retroHalftone dots, vintage badges, classic
sketch-notesHand-drawn, educational, warm
vector-illustrationFlat vector, black outlines, retro colors
vintageAged paper, historical, expedition style
warmFriendly, approachable, human-centered
watercolorSoft hand-painted, natural warmth

Detailed style definitions: references/styles/<style>.md

Auto Style Selection

When no --style is specified, system analyzes content to select best style:

Content SignalsSelected Style
Architecture, system design, engineeringblueprint
Product launch, keynote, marketing, brandbold-editorial
Education, classroom, tutorial, teachingchalkboard
Entertainment, creative, premium, cinematicdark-atmospheric
Technology explainer, science, researcheditorial-infographic
Storytelling, children, fantasy, magicalfantasy-animation
Technical docs, academic, bilingualintuition-machine
Personal story, emotion, growth, lifewarm
Simple, zen, focus, essentialminimal
Fun, easy, beginner, casualplayful
Nature, eco, wellness, health, organicnature
Pop culture, 80s/90s nostalgia, badgesretro
Product, SaaS, dashboard, productivitynotion
Productivity, workflow, app, tools, cuteflat-doodle
Gaming, retro tech, developer, 8-bitpixel-art
Educational, tutorial, knowledge sharingsketch-notes
Creative proposals, brand, toy-likevector-illustration
History, exploration, heritage, biographyvintage
Lifestyle, travel, food, personalwatercolor
Business, professional, strategy, analysiselegant

File Management

Output Directory

Each session creates an independent directory named by content slug:

cover-image/{topic-slug}/
├── source-{slug}.{ext}    # Source files (text, images, etc.)
├── prompts/
│   └── cover.md
└── cover.png

Slug Generation:

  1. Extract main topic from content (2-4 words, kebab-case)
  2. Example: "The Future of AI" → future-of-ai

Conflict Resolution

If cover-image/{topic-slug}/ already exists:

  • Append timestamp: {topic-slug}-YYYYMMDD-HHMMSS
  • Example: ai-future exists → ai-future-20260118-143052

Source Files

Copy all sources with naming source-{slug}.{ext}:

  • source-article.md (main text content)
  • source-logo.png (image from conversation)

Multiple sources supported: text, images, files from conversation.

Workflow

Step 1: Analyze Content

  1. Save source content (if not already a file):

- If user provides a file path: use as-is - If user pastes content: save to source.md in target directory

  1. Extract key information:

- Main topic: What is the article about? - Core message: What's the key takeaway? - Tone: Serious, playful, inspiring, educational? - Keywords: Identify style-signaling words

  1. Language detection:

- Detect source language from content - Detect user language from conversation context - Note if source_language ≠ user_language (will ask in Step 3)

Step 2: Determine Options

  1. Style selection:

- If --style specified, use that style - Otherwise, scan content for style signals and auto-select 3 candidates - Default to elegant if no clear signals

  1. Aspect ratio:

- If --aspect specified, use that ratio - Otherwise, prepare options: 2.35:1 (cinematic), 16:9 (widescreen), 1:1 (social)

Step 3: Confirm Options

Purpose: Let user confirm all options in a single step before generation.

IMPORTANT: Present ALL options in a single confirmation step using AskUserQuestion. Do NOT interrupt workflow with multiple separate confirmations.

Determine which questions to ask:

QuestionWhen to Ask
StyleAlways (required)
Aspect ratioAlways (offer common options)
LanguageOnly if source_language ≠ user_language

Present options (use AskUserQuestion with all applicable questions):

Question 1 (Style) - always:

  • Style A (recommended): [style name] - [brief description]
  • Style B: [style name] - [brief description]
  • Style C: [style name] - [brief description]
  • Custom: Provide custom style reference

Question 2 (Aspect) - always:

  • 2.35:1 Cinematic (Recommended) - ultra-wide, dramatic
  • 16:9 Widescreen - standard video/presentation
  • 1:1 Square - social media optimized

Question 3 (Language) - only if source ≠ user language:

  • [Source language] (matches content)
  • [User language] (your preference)

Language handling:

  • If source language = user language: Just inform user (e.g., "Title will be in Chinese")
  • If different: Ask which language to use for title text

Step 4: Generate Cover Concept

Create a cover image concept based on selected style:

Title (if included, max 8 characters):

  • Distill the core message into a punchy headline
  • Use hooks: numbers, questions, contrasts, pain points
  • Skip if --no-title flag is used

Visual Elements:

  • Style-appropriate imagery and icons
  • 1-2 symbolic elements representing the topic
  • Metaphors or analogies that fit the style

Step 5: Create Prompt File

Save prompt to prompts/cover.md with confirmed options.

All prompts are written in the user's confirmed language preference.

Prompt Format:

Cover theme: [topic in 2-3 words]
Style: [selected style name]
Aspect ratio: [confirmed aspect ratio]

[If title included:]
Title text: [8 characters or less, in confirmed language]
Subtitle: [optional, in confirmed language]

Visual composition:
- Main visual: [description matching style]
- Layout: [positioning based on title inclusion and aspect ratio]
- Decorative elements: [style-appropriate elements]

Color scheme:
- Primary: [style primary color]
- Background: [style background color]
- Accent: [style accent color]

Style notes: [specific style characteristics to emphasize]

[If no title:]
Note: No title text, pure visual illustration only.

Step 6: Generate Image

Image Generation Skill Selection:

  1. Check available image generation skills
  2. If multiple skills available, ask user to choose

Generation: Call selected image generation skill with prompt file, output path, and confirmed aspect ratio.

Step 7: Output Summary

Cover Image Generated!

Topic: [topic]
Style: [style name]
Aspect: [aspect ratio]
Title: [cover title] (or "No title - visual only")
Language: [confirmed language]
Location: [output path]

Preview the image to verify it matches your expectations.

Notes

  • Cover should be instantly understandable at small preview sizes
  • Title (if included) must be readable and impactful
  • Visual metaphors work better than literal representations
  • Maintain style consistency throughout the cover
  • Image generation typically takes 10-30 seconds
  • Title text uses user's confirmed language preference
  • Aspect ratio: 2.35:1 for cinematic/dramatic, 16:9 for widescreen, 1:1 for social media

Extension Support

Custom styles and configurations via EXTEND.md.

Check paths (priority order):

  1. .content-gen-skills/cover-image/EXTEND.md (project)
  2. ~/.content-gen-skills/cover-image/EXTEND.md (user)

If found, load before Step 1. Extension content overrides defaults.

平台分布

Claude Code

28.63%
按下载量换算58

Antigravity

23.38%
按下载量换算48

Gemini CLI

15.57%
按下载量换算32

windsurf

10.43%
按下载量换算21

trae

6.59%
按下载量换算13

OpenCode

3.41%
按下载量换算7

安全审计

暂无安全审计结果可展示。

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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