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Agent Skill · 图像处理

image-gen(图像生成器)

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。

image-gen 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 1,465。

总安装 264周安装 11GitHub Stars 公开资料未说明下载 88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:image-gen(图像生成器)
来源仓库:https://github.com/spillwavesolutions/image_gen
仓库路径:skills/image-gen
安装命令:
npx skills add spillwavesolutions/image_gen --skill "image-gen"
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 spillwavesolutions/image_gen --skill "image-gen"

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。

image-gen 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。通过 npx skills add spillwavesolutions/image_gen --skill "image-gen" 命令安装。

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。image-gen 属于图像处理类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/image-gen

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 spillwavesolutions/image_gen --skill "image-gen";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

image-gen 怎么安装?

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

image-gen 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。

image-gen 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。

image-gen 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。

image-gen 用的人多吗?

公开数据是累计安装 264 次,近一周安装 11 次,下载 88 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。

image-gen 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
image-gen

图像生成器 · 本页

264—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

Image Gen

Contents

- Step 1: Analyze Article Content - Step 2: Generate Cover Image - Step 3: Generate In-Article Images - Step 4a: Integrate Images - Step 4b: Write ALT Text - Step 5: Verify and Save

Overview

Generate high-quality images for technical articles using the imagen CLI tool (powered by gemini-2.5-flash-image). This skill provides a systematic workflow for creating two types of images:

  1. Cover Images: High-impact, conceptual images that grab attention on LinkedIn/Medium
  2. In-Article Images: Technical diagrams and illustrations that explain specific concepts

The skill includes comprehensive prompt engineering guidance and best practices for integrating images with SEO-friendly ALT text.

When to Use This Skill

Invoke this skill when:

  • Creating visual assets for a completed or near-complete article
  • User requests "generate images for this article" or similar
  • Article needs a cover image for publication
  • Technical concepts would benefit from visual explanation
  • Breaking up long text sections with relevant imagery
  • Optimizing article for LinkedIn/Medium with visual appeal

Typical workflow position: After article content is finalized (Phase 8 in the article enhancement workflow), before SEO optimization.

Workflow

Step 1: Analyze Article Content

Before generating any images, analyze the article to identify:

  1. Article topic and key themes: What is the main subject?
  2. Key concepts needing visualization: Which technical ideas are complex or abstract?
  3. Section breaks: Where would images improve readability?
  4. Target audience: Developers? DevOps? Beginners or advanced?

Output: List of 2-4 images needed (1 cover + 1-3 in-article)

Example:

Article: "Mastering Alembic for Database Migrations"
Images needed:
- Cover: Conceptual image representing database evolution/migration
- Image 1: Diagram showing migration workflow
- Image 2: Visual comparing manual SQL vs Alembic automation

Step 2: Generate Cover Image

Cover images should be high-impact, conceptual, and visually interesting to grab attention. They are often metaphorical rather than literal.

Prompt Engineering for Covers:

  • Style keywords: digital art, 3D render, conceptual art, abstract
  • Atmosphere: cinematic lighting, dramatic, futuristic, professional
  • Composition: Specify angle, focus, and elements
  • Structure: [Style] cover image of [Metaphor/Concept] representing [Article Topic], [Atmosphere/Lighting], [Composition]

Command:

imagen generate "DETAILED PROMPT" --output work/images/[article_name]_cover.png

Example Prompts:

For a Vertex AI article:

imagen generate "A stunning digital art cover image showing three glowing pathways converging into a central AI cloud platform. Each pathway is a different color (green, blue, gold) representing different AI models flowing into Google Cloud infrastructure. The scene has dramatic cinematic lighting with a futuristic tech aesthetic. Style: conceptual, 3D render, high-detail, professional." --output work/images/vertex_ai_cover.png

For an Alembic article:

imagen generate "A dramatic 3D render showing a database schema transforming like evolving architecture, with migration files as glowing blueprints guiding the transformation. Dark background with cinematic lighting highlighting the evolution process. Style: conceptual art, digital art, high-detail, professional." --output work/images/alembic_cover.png

Tips:

  • Be specific and detailed (100+ words is fine)
  • Use metaphors that resonate with the topic
  • Specify lighting/atmosphere for mood
  • Include "professional" or "high-detail" for quality

Step 3: Generate In-Article Images (1-3)

In-article images should explain or reinforce specific concepts from the text. They are more direct and educational than cover images.

Prompt Engineering for In-Article Images:

  • Style keywords: technical diagram, blueprint, minimalist illustration, clean
  • Clarity: clear labels, connecting arrows, color-coded, organized
  • Purpose: Focus on explaining one specific concept
  • Structure: [Style] showing [Specific Concept], [Visual Elements], [Labels/Clarity]

Command:

imagen generate "CONCEPT-SPECIFIC PROMPT" --output work/images/[article_name]_[concept].png

Example Prompts:

For a technical diagram:

imagen generate "A clean technical diagram showing three distinct client libraries connecting to a central Vertex AI platform. Use color-coded arrows: green for native Google SDK, blue for partner Anthropic SDK, and gold for OpenAI-compatible SDK. Include clear labels for each connection path. Style: blueprint, technical diagram, clear labels, professional." --output work/images/vertex_ai_three_patterns.png

For a comparison illustration:

imagen generate "A minimalist side-by-side comparison showing traditional infrastructure (left) with tangled wires and manual configuration versus modern infrastructure-as-code (right) with clean, organized flow. Use contrasting colors and simple icons. Style: clean, minimalist illustration, symbolic." --output work/images/traditional_vs_iac.png

For a workflow diagram:

imagen generate "A flowchart-style diagram showing the Alembic migration workflow: 1) Model changes → 2) Auto-generate migration → 3) Review migration → 4) Apply to database. Use arrows connecting each step with clear labels. Style: blueprint, technical flowchart, organized, clean." --output work/images/alembic_workflow.png

Tips:

  • Focus on one concept per image
  • Use color-coding to distinguish elements
  • Request "clear labels" or "connecting arrows" for clarity
  • Simpler is often better for technical diagrams

Step 4a: Integrate Images

CRITICAL: Integrate generated images into the article at strategic locations.

Integration Checklist:

  1. Create work/images/ directory if needed
  2. Verify all images generated successfully (cover + in-article)
  3. Add cover image immediately after H1 title
  4. Add in-article images at strategic section breaks
  5. Save updated article as new version (e.g., v8_with_images.md)

Markdown Integration Format:

# Article Title

![Cover image description here](images/article_cover.png)

## Introduction

Text introducing the problem...

![Diagram description here](images/article_diagram.png)

Step 4b: Write ALT Text

Write descriptive ALT text (50-125 characters) for each image to ensure accessibility and SEO.

Good ALT Text (descriptive, specific):

  • "Architecture diagram showing Cloud Run connecting through VPC Connector to AlloyDB in private subnet"
  • "Comparison showing manual infrastructure with tangled wires versus automated infrastructure-as-code"
  • "Flowchart illustrating Alembic migration workflow from model changes to database update"

Bad ALT Text (vague, non-descriptive):

  • "diagram" or "image"
  • "architecture" (too vague)
  • "image1.png" or "screenshot"

Step 5: Verify and Save

Final checks:

  1. All images generated successfully (check file paths)
  2. Images linked correctly in markdown
  3. ALT text is descriptive and SEO-friendly (50-125 chars)
  4. Cover image placed after H1 title
  5. In-article images at logical section breaks
  6. New version saved (e.g., work/draft/article_v8_with_images.md)

Typical outputs:

  • 1 cover image (*_cover.png)
  • 1-3 in-article images (*_concept.png, *_workflow.png, etc.)
  • Updated article with integrated images and ALT text

Command Reference

Basic Usage:

imagen generate "PROMPT" --output FILENAME.png

Directory Setup:

mkdir -p work/images

Batch Generation Example:

# Cover
imagen generate "COVER PROMPT" --output work/images/article_cover.png

# In-article images
imagen generate "DIAGRAM PROMPT" --output work/images/article_diagram.png
imagen generate "COMPARISON PROMPT" --output work/images/article_comparison.png

Prompt Engineering Best Practices

For comprehensive prompt engineering guidance, refer to references/prompting_guide.md.

Core Principles:

  1. Be Specific: Detailed descriptions produce better results
  2. Define Style: Always specify artistic style (digital art, blueprint, etc.)
  3. Set Atmosphere: Use lighting and mood keywords
  4. Use Photography Terms: wide-angle, close-up, depth of field, etc.

Cover vs In-Article Summary:

AspectCover ImagesIn-Article Images
GoalGrab attention, create "wow" factorExplain concepts, reinforce learning
Styledigital art, 3D render, conceptual arttechnical diagram, blueprint, minimalist
ApproachMetaphorical, abstractDirect, educational
Keywordscinematic, dramatic, futuristicclean, clear labels, organized

Common Patterns

Pattern 1: Simple Article (1-2 images)

  • Cover image only
  • OR Cover + 1 key diagram

Pattern 2: Standard Article (2-3 images)

  • Cover image (conceptual)
  • 1-2 in-article images (technical diagrams)

Pattern 3: Complex Tutorial (3-4 images)

  • Cover image (conceptual)
  • Workflow/architecture diagram
  • Comparison illustration
  • Example/output visualization

Resources

references/prompting_guide.md

Complete guide to prompt engineering for the imagen CLI, including:

  • Detailed prompt crafting principles
  • Style and medium keywords
  • Lighting and atmosphere techniques
  • Photography/cinematography terms
  • Extensive examples for different image types

Load this reference when crafting complex prompts or needing inspiration for visual concepts.

平台分布

Claude Code

28.06%
按下载量换算25

Antigravity

20.52%
按下载量换算18

Gemini CLI

16.73%
按下载量换算15

windsurf

13.22%
按下载量换算12

OpenCode

8.17%
按下载量换算7

Codex

3.16%
按下载量换算3

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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