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Agent Skill · 研究检索

design-system(设计系统)

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

design-system 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,674 个 Skill 里排第 59,221。

总安装 392周安装 16GitHub Stars 124下载 125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:design-system(设计系统)
来源仓库:https://github.com/kenneth-liao/ai-launchpad-marketplace
仓库路径:skills/design-system
安装命令:
npx skills add https://github.com/kenneth-liao/ai-launchpad-marketplace --skill design-system
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/kenneth-liao/ai-launchpad-marketplace --skill design-system

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

design-system 用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化,适合在 Codex、Claude、Cursor、Gemini CLI 中生成 UI 方案或改进组件层级。适用于产品页面结构整理、视觉一致性检查和响应式表现验证。

通过 npx skills add 命令从指定 GitHub 仓库安装使用。使用时需结合现有品牌和设计系统,避免仅堆砌装饰元素。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/design-system

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/kenneth-liao/ai-launchpad-marketplace --skill…;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

design-system 怎么安装?

在终端执行 npx skills add https://github.com/kenneth-liao/ai-launchpad-marketplace --skill design-sys…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

design-system 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。

design-system 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。

design-system 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。

design-system 用的人多吗?

公开数据是累计安装 392 次,近一周安装 16 次,下载 125 次,GitHub 124 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。

design-system 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
design-system

设计系统 · 本页

392124需要联网未明确有提醒

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

Design System Generator

Create complete visual design systems from scratch through guided discovery, documentation, and AI-generated asset production.

Workflow Overview

Execute these phases in strict order. Output Location must be asked first. Phase 0 is optional (skip if user has no references). Never skip Phases 1-5. Each phase builds on the previous.

PhaseNameActionOutput
—Output LocationAsk where to save the design systemoutput_location = "local" or "user"
0Reference InputCollect + analyze user reference imagesVisual analysis + smart defaults for discovery
1DiscoveryInteractive questionnaireUser preferences across 10 dimensions
2SynthesisAnalyze + name the styleStyle name, core principles, full spec
3DocumentationGenerate style guide{style-name}-design-system.md
4Asset GenerationGenerate images via creator-stack:nanobanana8 PNG style board elements
5AssemblyOrganize + presentComplete design system directory

Output Location

Before anything else, ask the user where they want the design system saved. Use the AskUserQuestion tool:

Question: "Where should this design system be saved?"

OptionDescription
Local project (current directory)Saves to ./design-system/ in the current working directory. Best when this design system is specific to one project.
User level (system-wide)Saves to ~/.claude/.context/design-systems/{style-name-slug}/. Available across all projects and conversations. Best for brand-wide design systems you'll reuse everywhere (e.g., your YouTube brand, your newsletter brand).

Store the choice as output_location.

Path resolution (happens after Phase 2 when the style name is finalized):

  • Local: {output_dir} = ./design-system/
  • User level: {output_dir} = ~/.claude/.context/design-systems/{style-name-slug}/

Where {style-name-slug} is the style name lowercased with spaces and special characters replaced by hyphens (e.g., "Ink & Ember" → ink-and-ember, "Neon Chalk" → neon-chalk).

User-level design systems are organized so each style gets its own directory:

~/.claude/.context/design-systems/
├── ink-and-ember/          ← YouTube brand
│   ├── ink-and-ember-design-system.md
│   ├── 01-hero-character.png
│   └── ...
├── paper-and-sage/         ← Newsletter brand
│   ├── paper-and-sage-design-system.md
│   ├── 01-hero-character.png
│   └── ...

Phase 0: Reference Input (Optional)

Before starting discovery, ask the user if they have existing visual references to anchor the design system. References dramatically improve consistency by grounding the system in concrete examples rather than abstract descriptions alone.

Opening prompt: "Before we start defining your design system, do you have any existing visual references? These could be brand assets you already use, inspiration images, or examples of styles you like. This is optional — we can build entirely from scratch too."

Supported input modes:

ModeHow to ProvideWhat Happens
Folder pathUser provides a path like ~/brand-assets/ or ./images/Read all image files in the folder (PNG, JPG, SVG, WebP). Limit to 10 most relevant if more are provided.
Individual filesUser provides one or more file pathsRead each image directly.
Website URLUser provides a URL like https://mybrand.comUse WebFetch to capture the page, then analyze the visual design (colors, typography, layout, imagery style).
Direct pasteUser pastes or drags images into the conversationAnalyze the images as provided.
SkipUser says they have no referencesProceed directly to Phase 1 with no smart defaults.

Analysis protocol:

For each reference image or website, extract and document:

  1. Dominant colors — Identify the 3-5 most prominent colors with approximate hex codes. Note which appear to be background, primary, and accent.
  2. Line work / rendering style — Is it illustrated or photographic? If illustrated: line weight (thick/thin), edge quality (clean/sketchy), fill approach (flat/gradient/outline-only).
  3. Composition patterns — Spacing density, focal point placement, symmetry, use of whitespace.
  4. Medium / aesthetic — Flat vector, hand-drawn, 3D, photographic, collage, abstract, etc.
  5. Mood / emotional tone — What feeling does it convey? Warm, corporate, playful, dark, etc.
  6. Character style (if characters present) — Proportions, facial detail level, body style, identifying features.
  7. What's NOT present — Notable absences that may indicate intentional anti-patterns (no gradients, no photography, no text, etc.).

After analysis, present a summary:

"Here's what I'm seeing across your references: [2-3 sentence synthesis of the dominant visual patterns — colors, style, mood, composition]. I'll use this to suggest defaults during the discovery questionnaire, but you can override any suggestion."

Smart defaults:

  • Store the analysis results as reference_analysis
  • During Phase 1, for each dimension where the reference analysis provides a clear signal, pre-select the closest matching option and note: *"Based on your references, I'd suggest: [option] — [brief reason from analysis]. Does this match your intent?"*
  • If the references are ambiguous for a dimension (e.g., mixed styles across images), present all options without a default and note the ambiguity: *"Your references show a mix of [X] and [Y] — which direction do you want to lean?"*
  • The user always has full control — smart defaults are suggestions, not decisions

Reference images are preserved for later use:

  • Copy user-provided reference images to design-system/references/ during Phase 5
  • These become part of the Reference Library alongside the 8 generated style board images
  • During Phase 4 asset generation, user references can be provided to nanobanana as style anchors

Phase 1: Discovery

Guide the user through structured questions to define their visual preferences. Use the AskUserQuestion tool to present options.

Load the full question bank from references/discovery-framework.md.

Rules:

  • Ask questions in dimension order (they build on each other)
  • Present 3-4 options per question with clear descriptions
  • Allow multi-select where the framework indicates
  • If Phase 0 produced smart defaults, pre-select the suggested option and include the reasoning. Still present all options — the user decides.
  • After each answer, give a brief 1-sentence acknowledgment contextualizing the choice, then move to the next question
  • Adapt later questions based on earlier answers (the framework specifies when to skip or modify questions)
  • Complete ALL dimensions before moving to Phase 2
  • Batch related questions when possible (max 4 per AskUserQuestion call) to keep the flow efficient without overwhelming

Dimensions (in order):

  1. Primary use cases
  2. Overall vibe / mood
  3. Medium preference (illustration vs photography)
  4. Specific illustration style direction
  5. Color strategy
  6. Accent color
  7. Base tone
  8. Line work / edge treatment
  9. Composition approach
  10. Anti-patterns (what to avoid)

Phase 2: Synthesis

After all 10 dimensions are answered, synthesize into a coherent design system.

Steps:

  1. Review all discovery answers as a complete set
  2. Identify the dominant aesthetic thread connecting the choices
  3. Generate a memorable 2-3 word style name using the naming convention below
  4. Define 3-4 core principles — short imperative phrases with explanations
  5. Build the complete color palette — 6 colors with hex codes, role names, usage descriptions, AND natural language AI descriptions (see template)
  6. Calculate color ratios based on strategy (see ratio guide in template)
  7. Build the Style Language Map — translate every technical spec (colors, line work, fill, texture, composition, mood) into copy-paste-ready natural language phrases for prompt use. This is critical for AI generation consistency.
  8. Specify line work, illustration, typography, and composition rules
  9. Define the Character System — including system type (Solo, Duo/Companion, or Cast). For each character: archetype, proportions, strict facial feature rules (what IS present AND what is FORBIDDEN), consistent identifiers, and fidelity levels. For Duo systems: define companion appearance, states/behaviors, and which character owns the accent color. See template for full structure.
  10. Define application guidelines for each use case from Dimension 1
  11. List explicit anti-patterns from Dimension 10 plus any that conflict with chosen directions
  12. Create the Consistency Enforcement section — document unwanted feature prevention rules, style drift prevention keywords, and a character verification checklist (see template)

Style Naming Convention: Combine a texture word + a color/mood word. The name should evoke the visual feel in 2-3 words.

Texture WordsColor/Mood Words
Ink, Chalk, Pixel, Neon, PaperTeal, Coral, Sunset, Midnight, Forest
Brush, Wire, Grain, Sketch, FoilOcean, Ember, Frost, Clay, Bloom
Velvet, Stone, Glass, Thread, StampSage, Copper, Slate, Ivory, Plum

Examples: "Ink & Teal", "Neon Chalk", "Warm Blueprint", "Velvet Ember", "Paper & Sage"

Present the style name and core principles to the user for approval before proceeding to Phase 3. If the user wants changes, adjust and re-present.


Phase 3: Documentation

Generate the complete design system document using the template from references/design-system-template.md.

Output: A markdown file saved to {output_dir}/{style-name}-design-system.md (see Output Location for path resolution).

Rules:

  • Fill EVERY section — no placeholders or template markers in the final output
  • Include specific hex codes for all colors
  • Write in present tense, declarative voice
  • Include concrete, actionable guidelines (not vague suggestions)
  • The document must be fully self-contained — anyone reading it should be able to produce on-brand visuals without additional context
  • Include the complete Nano Banana prompt library (8 prompts) in the document

Verification: After writing the document, read it back and check:

  • No unfilled {{placeholder}} markers remain
  • All sections from the template are present
  • All 6 color palette entries have hex codes
  • The Nano Banana prompt library has all 8 prompts
  • The Style Language Map is complete (no empty categories)
  • If any issues found, fix and re-write before proceeding to Phase 4

Phase 4: Asset Generation

Generate 8 style board elements using the creator-stack:nanobanana skill. Build prompts using the templates and best practices from references/prompt-engineering.md.

Required elements (generate in this order):

#ElementAspect RatioDescription
1Hero character/mascot1:1The signature illustrated element
2Concept icon1:1A single idea visualized
3Framework diagram16:9Connected nodes or flow
4Social media asset1:1A standalone icon for posts
5Background texture16:9Subtle, usable background
6Sticker/badge1:1Compact element, transparent bg
7Pattern element1:1Repeating doodles or motifs
8Character scene1:1Person or figure in context

For each element:

  1. Write a detailed narrative prompt following the templates in prompt-engineering.md
  2. Embed the exact hex codes, line style, and composition rules from the design system
  3. Specify the correct aspect ratio from the table above
  4. If Phase 0 provided user references, select the 1-2 most relevant reference images for this element type and provide them to nanobanana as style anchors (see prompt-engineering.md "Using User-Provided References" section)
  5. Use the creator-stack:nanobanana skill to generate the image
  6. Save the output to the {output_dir} directory with a descriptive filename

Prompt construction rules:

  • Write as descriptive narrative paragraphs (NOT keyword lists)
  • Specify background color by name AND hex code — AI generators interpret "white" differently, but #FFFFFF is unambiguous
  • Describe the line/stroke style explicitly — without this, models default to their own aesthetic and you lose style consistency across the 8 elements
  • Constrain accent color usage ("the only color in the entire image") — unconstrained color leads to palette drift that compounds across the series
  • End with format/aspect ratio — placing dimensions last ensures the model treats them as hard constraints rather than suggestions
  • Include explicit exclusions ("No text, no gradients, no other colors") — models add elements opportunistically unless told not to
  • Reference the artistic tool metaphor from the design system (brush pen, marker, pencil, etc.) — tool metaphors anchor the rendering style more reliably than abstract adjectives like "clean" or "bold"

Naming convention for generated files:

{output_dir}/01-hero-character.png
{output_dir}/02-concept-icon.png
{output_dir}/03-framework-diagram.png
{output_dir}/04-social-media-asset.png
{output_dir}/05-background-texture.png
{output_dir}/06-sticker-badge.png
{output_dir}/07-pattern-element.png
{output_dir}/08-character-scene.png

Phase 5: Assembly

Organize all outputs and present the complete system to the user.

Final directory structure:

For local (output_location = local):

./design-system/
├── {style-name}-design-system.md
├── 01-hero-character.png
├── ...
├── 08-character-scene.png
└── references/              ← only if Phase 0 provided user references

For user level (output_location = user):

~/.claude/.context/design-systems/{style-name-slug}/
├── {style-name}-design-system.md
├── 01-hero-character.png
├── ...
├── 08-character-scene.png
└── references/              ← only if Phase 0 provided user references

Final steps:

  1. List all generated files with brief descriptions and the full output path
  2. Display the style board layout diagram (from the design system document)
  3. Establish the Reference Library — present the 8 generated images as canonical style references. Explain that these images should be provided as style references when generating future assets (using nanobanana's multi-image reference capability) to maintain visual consistency beyond what text prompts alone achieve.
  4. Run the Verification Checklist against each generated image:

- Does the color palette match? (check accent color, base tone, ink colors) - Is the line weight/style consistent with the design system spec? - Does the composition follow the defined rules? - Are anti-patterns absent? - Does the overall mood match the Style Language Map? - Character facial features: Do characters have ONLY the allowed features? Check for unwanted noses, eyebrows, ears, or other forbidden features. This is the most common failure — verify every face. - Companion character (if Duo system): Is the companion present? Is it the correct size relative to the primary character? Is it the ONLY accent-colored element? Flag any images that fail verification and offer to regenerate them.

  1. Ask the user: "Want to regenerate or adjust any elements?"
  2. Offer to generate additional element types or variations
  3. If the user is satisfied, confirm the design system is complete
  4. If user-level: Remind the user that this design system is now available system-wide. In any future Claude Code session, they (or a future asset-generation skill) can reference it at ~/.claude/.context/design-systems/{style-name-slug}/

Updating an Existing Design System

If the user already has a design system document, read it first before starting.

Update workflow:

  1. Read and summarize the existing design system
  2. Ask the user what they want to change (skip full discovery — only ask about the dimensions being modified)
  3. Re-synthesize only the affected aspects
  4. Update the design system document (preserve unchanged sections)
  5. Regenerate only the assets affected by the changes
  6. Preserve unchanged elements and filenames

Error Handling

  • If nanobanana generation fails, retry once with a simplified prompt
  • If the user is unhappy with a generated element, ask what specifically to change and regenerate with an adjusted prompt
  • If the user's preferences conflict (e.g., "minimalist" + "dense and detailed"), flag the tension during synthesis and ask which direction to prioritize
  • If the output directory does not exist, create it (including parent directories for user-level paths)
  • If a design system with the same slug already exists at the user level, ask the user whether to overwrite or choose a different name

平台分布

Codex

36.67%
按下载量换算46

Claude

27.15%
按下载量换算34

Cursor

18.24%
按下载量换算23

Gemini CLI

10.12%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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