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Agent Skill · 图像处理

concept-to-image(概念到图像)

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。

concept-to-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,权限为操作浏览器;许可证信息还不明确,第三方扫描已通过,按安装量在图像处理类的 1,562 个 Skill 里排第 1,226。

总安装 759周安装 31GitHub Stars 217下载 243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:concept-to-image(概念到图像)
来源仓库:https://github.com/mathews-tom/praxis-skills
仓库路径:skills/concept-to-image
安装命令:
npx skills add https://github.com/mathews-tom/praxis-skills --skill concept-to-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。

skills.shnpx skills
npx skills add https://github.com/mathews-tom/praxis-skills --skill concept-to-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。

通过 HTML/CSS/SVG 中间层生成高质量视觉素材,支持 PNG 和 SVG 导出。适合将抽象概念转化为可视化内容,利用可编辑的 HTML 层进行精细化调整。使用 Playwright 脚本实现从代码到图像的自动化转换流程。安装前需确认权限范围和维护状态,注意是否涉及联网、命令执行或文件读写操作。

concept-to-image 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/concept-to-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 https://github.com/mathews-tom/praxis-skills --skill concept-to-i…;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

    它需要操作浏览器,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

concept-to-image 怎么安装?

在终端执行 npx skills add https://github.com/mathews-tom/praxis-skills --skill concept-to-image。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

concept-to-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。

concept-to-image 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

concept-to-image 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。

concept-to-image 用的人多吗?

公开数据是累计安装 759 次,近一周安装 31 次,下载 243 次,GitHub 217 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。

concept-to-image 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 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

  • 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。

不太适合

  • 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。

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
concept-to-image

概念到图像 · 本页

759217操作浏览器未明确通过

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

Concept to Image

Creates polished visuals from concepts using HTML/CSS/SVG as a refineable intermediate, then exports to PNG or SVG.

Reference Files

FilePurpose
references/design-guide.mdDesign patterns, anti-patterns, color palettes, typography choices, layout examples
scripts/render_to_image.pyPlaywright-based export script — takes HTML in, PNG or SVG out
assets/template.htmlBase HTML template with .canvas container and CSS custom properties pre-configured

Why HTML as intermediate

HTML is the refineable layer between idea and image. Unlike direct canvas rendering, the user can see the HTML artifact, request changes ("make the title bigger", "swap the colors", "add a third column"), and only export once satisfied. This makes the workflow iterative and controllable.

Workflow

Concept → HTML artifact (view + refine) → PNG or SVG export
  1. Interpret the user's concept — determine what kind of visual best fits (diagram, infographic, card, chart, etc.)
  2. Design a self-contained HTML file using inline CSS and inline SVG — zero external dependencies
  3. Present the HTML as an artifact so the user can preview and request refinements
  4. Iterate on the HTML based on user feedback (colors, layout, content, sizing)
  5. Export to PNG and/or SVG when the user is satisfied, using scripts/render_to_image.py

Step 1: Interpret the concept

Determine the best visual format:

User intentVisual formatApproach
Explain a process/flowFlowchart or pipeline diagramSVG paths + boxes
Compare itemsSide-by-side or matrixCSS Grid
Show hierarchyTree or layered diagramNested containers + SVG connectors
Present dataChart or infographicSVG shapes + data labels
Social/marketing graphicCard or posterTypography-forward HTML/CSS
Icon, logo, badgeCompact symbolPure SVG
Educational conceptAnnotated diagramSVG + positioned labels

Step 2: Design the HTML

Read references/design-guide.md for detailed design patterns and anti-patterns.

Core rules:

  • Single file, self-contained: All CSS inline in <style>, all graphics as inline <svg>. No external resources.
  • Fixed viewport: Set explicit width and height on the root container matching the intended export size. This is critical — Playwright screenshots the element at this exact size.
  • Anti-AI-slop: Avoid centered-everything layouts, purple gradients, uniform rounded corners, and Inter/system font defaults. See design guide for alternatives.
  • SVG-first for shapes: Use inline SVG for icons, connectors, shapes, and any element that should scale cleanly. CSS for layout and typography.
  • Color with intention: 3-4 hues max + neutrals. Define as CSS custom properties. Every color encodes meaning.
  • Start from the template: Use assets/template.html as the base structure.

Sizing guidelines

Use caseRecommended size
Social media graphic1200×630
Infographic (portrait)800×1200
Presentation slide1920×1080
Square post1080×1080
Icon/badge256×256 or 512×512
Wide diagram1600×900

Set the .canvas container to the chosen size. The export script captures this element.

Step 3: Present and iterate

Present the HTML file to the user. They'll see it rendered as an artifact. Common refinement requests:

  • Color/theme changes → update CSS custom properties
  • Layout adjustments → modify grid/flexbox
  • Content changes → edit text/SVG elements
  • Size changes → update .canvas dimensions

Each iteration is a quick HTML edit, not a full re-render. This is the key advantage over direct image generation.

Step 4: Export to image

Once the user is satisfied, run the export script:

python3 scripts/render_to_image.py <input.html> <output.png|.svg> [--width 1200] [--height 630] [--scale 2] [--selector ".canvas"]

Parameters

ParamDefaultDescription
input(required)Path to HTML file
output(required)Output path. Extension determines format (.png or.svg)
--widthautoViewport width (overrides HTML-defined size)
--heightautoViewport height (overrides HTML-defined size)
--scale2Device scale factor for PNG (2 = retina quality)
--selector.canvasCSS selector for the element to capture
--full-pagefalseCapture the full page instead of a specific element

PNG export

Uses Playwright to launch headless Chromium and screenshot the .canvas element at the specified scale factor. Scale 2 produces retina-quality output (e.g., 1200×630 CSS pixels → 2400×1260 PNG).

SVG export

Two strategies, chosen automatically:

  1. SVG-native content: If the .canvas element contains a single root <svg>, extracts it directly as a clean SVG file. This produces a true vector SVG.
  2. HTML-based content: If the content is CSS/HTML-heavy, falls back to PNG export with a note that true SVG requires SVG-native design. The script will warn and suggest redesigning with SVG elements if vector output is needed.

Delivering the output

Present the output file to the user. Always deliver both the HTML (for future editing) and the image (final output).

Error Handling

ErrorCauseResolution
playwright not foundPlaywright package not installedRun npx playwright install chromium or pip install playwright && playwright install chromium
Browser launch failureHeadless Chromium fails to startVerify --headless mode is supported; check available memory (Chromium needs ~200 MB)
.canvas selector not foundHTML does not contain an element matching .canvasVerify assets/template.html was used as the base; check the root container has class="canvas"
Render timeoutComplex HTML takes too long to render before screenshotIncrease the timeout via --timeout flag in the script, or simplify the HTML (reduce DOM depth, inline fewer SVGs)
SVG export falls back to PNG.canvas element contains HTML/CSS content, not a root SVGSee SVG export section; redesign with a single root <svg> if vector output is required

Limitations

  • Playwright + Chromium required — the export script cannot run without a working Chromium installation.
  • macOS and Linux only for headless browser export. Windows Subsystem for Linux works; native Windows Playwright may require separate setup.
  • SVG export is best-effort — complex HTML/CSS layouts fall back to PNG. True vector SVG requires a single root <svg> as the .canvas child.
  • Max viewport 4096×4096 — Chromium refuses screenshots larger than this. Use --scale to achieve higher effective resolution within this limit.
  • No animation support — exported images are static snapshots. CSS animations and JavaScript-driven transitions are frozen at their initial state.

Output Example

After a successful export, the script prints the output path and file stats:

Exported: concept-diagram.png
  Size:       2400 × 1260 px  (2× scale from 1200 × 630 canvas)
  File size:  ~180 KB
  Format:     PNG (RGBA)

Filename pattern follows whatever was passed as the output argument. Typical file sizes:

  • Simple diagrams (text + shapes): 80–200 KB
  • Dense infographics with gradients: 300–600 KB
  • Full 1920×1080 at 2× scale: 500 KB–1.5 MB

Design anti-patterns to avoid

These produce generic "AI-generated" looking output:

  • Centered everything with equal spacing
  • Purple/blue gradient backgrounds
  • Uniform border-radius on all elements
  • Generic icon libraries (use custom inline SVG)
  • System font stack without typographic intention
  • Drop shadows on everything
  • Low information density (too much whitespace)

Font handling

Since this environment has limited font access, use web-safe font stacks with intentional fallbacks:

  • Technical/mono: 'Courier New', 'Consolas', monospace
  • Clean sans: 'Helvetica Neue', 'Arial', sans-serif
  • Editorial serif: 'Georgia', 'Times New Roman', serif
  • Display: Use SVG text with custom paths for display typography when needed

平台分布

Codex

37.27%
按下载量换算91

Claude

28.81%
按下载量换算70

Cursor

17.82%
按下载量换算43

Gemini CLI

8.43%
按下载量换算20

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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