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Agent Skill · 前端设计

interior-design(室内设计)

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。

interior-design 是前端设计类 Agent Skill,可用宿主为 Local Agent,通过unknown获取,权限为只读;许可证信息还不明确,暂无第三方扫描结果,按安装量在前端设计类的 10,216 个 Skill 里排第 8,640。

总安装 269周安装 11下载 87核验 2026-05-01
前端设计只读unknown未标认证来源可访问许可证需确认审计未展示Local Agent

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。
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:interior-design(室内设计)
来源仓库:https://skills.volces.com
仓库路径:interior-design
安装命令:
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。当前暂无明确安装命令,请以来源页面说明为准。

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

interior-design 用于辅助界面设计、视觉规范和交互体验优化,支持空间设计场景。它适合让 Agent 生成布局方案、配色建议或家具摆放示意图。使用时需结合户型图和用户需求,Agent 将输出可读的设计说明或草图描述。涉及真实装修时应核对建材品牌和施工标准,避免推荐非标或高风险方案。

安装前请确认是否调用渲染引擎,确保输出符合本地硬件性能限制。

来源仓库内路径:interior-design

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 Local Agent;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

    没有现成安装命令,按unknown的说明从来源页面获取,仓库路径是 interior-design。

  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

interior-design 怎么安装?

公开资料没有给出可以直接复制的命令,需要按来源页面说明手动安装,仓库内路径为 interior-design。

interior-design 支持哪些 AI 工具?

公开资料标注支持 Local Agent。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。

interior-design 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。

interior-design 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。

interior-design 用的人多吗?

公开数据是累计安装 269 次,近一周安装 11 次,下载 87 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。

interior-design 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

  • 专注 Local Agent 一种宿主,触发方式和使用习惯不用来回切换。
  • 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

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Local Agent,想直接扩展它能力的人。
  • 需要处理前端设计类任务、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

  • 需要明确授权才能用到公司项目里的场景。
  • 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。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
interior-design

室内设计 · 本页

269—只读未明确未收录

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

When to Use

User needs help with interior spaces: renovation planning, furniture selection, material calculations, rental optimization, staging, or product visualization in rooms.

Architecture

Project data in ~/interior-design/. See memory-template.md for setup.

~/interior-design/
|-- memory.md          # HOT: active project, confirmed preferences
|-- spaces/            # Per-room: dimensions, fixed elements, constraints
|-- suppliers.md       # Verified local suppliers with price tiers
+-- archive/           # Completed projects

Data Storage

All data stored in ~/interior-design/. Create on first use:

mkdir -p ~/interior-design/{spaces,archive}

Quick Reference

TopicFile
Memory setupmemory-template.md
Material mathcalculations.md
Style matchingstyles.md
Staging/rentalsstaging.md
Photo optimizationphotography.md
Room-specificspaces.md

Scope

This skill ONLY:

  • Advises based on user-provided dimensions and photos
  • Calculates quantities from explicit measurements
  • Stores preferences in local files
  • Compares options within stated constraints

This skill NEVER:

  • Makes purchases or contacts suppliers
  • Infers style from silence
  • Suggests products without confirming user's region
  • Recommends specific items without verifying availability

Self-Modification

This skill NEVER modifies its own SKILL.md. Learned preferences stored in ~/interior-design/memory.md.

Core Rules

1. No Dimensions = No Specifics

The model defaults to suggesting "standard" furniture. There is no standard.

Before any furniture/layout recommendation:

[ ] Room dimensions (L x W x H) in user's unit system
[ ] Door dimensions (will large items fit through?)
[ ] Window positions (affects layout and lighting)
[ ] What MUST stay (existing pieces, built-ins)

Without these -> give only directional guidance, never specific products or layouts.

2. Localize Before Recommending

Models suggest globally-known brands (IKEA, West Elm, Wayfair) regardless of user location.

Verification sequence:

  1. Ask user's country/city
  2. Confirm which retailers are accessible
  3. Check if suggested items ship there with reasonable cost/time
  4. Note price differences (IKEA Spain!= IKEA USA)

Never recommend -> "Buy X from Y" without confirming Y operates in user's region.

3. Price Tier Lock

Models mix budget and premium items in the same proposal, creating incoherent spaces.

Establish tier ONCE, then stay in it:

Signal from userLock to tier
"affordable", "budget", "IKEA level"Budget only
"quality", "investment", specific mid-brandsMid-range only
"designer", brand names, no price concernPremium only

If user has €200 sofa -> all suggestions must fit €200-sofa-world.

4. Entry Path Verification

Models suggest items that won't physically enter the space.

Before recommending any item >50cm in any dimension:

  • Ask about entry points (door width, stairwell, elevator)
  • Calculate diagonal fit for sofas/mattresses
  • Flag items that require assembly-on-site vs delivered-assembled

"This sofa is perfect" -> useless if it doesn't fit through a 75cm door.

5. Dependency Sequencing

Models suggest purchases without considering what must happen first.

Interior work has hard sequences:

Structural -> Electrical/Plumbing -> Surfaces -> Fixed furniture -> Movable -> Decor

Never recommend:

  • Flooring before confirming subfloor is level
  • Lighting fixtures before electrical points are defined
  • Paint colors before confirming lighting (natural/artificial)
  • Furniture before flooring is installed (delivery damages)

6. Photography Impact Awareness

For rentals/staging: every design decision affects listing photos.

Photo-first thinking:

  • Hero shot (first image) determines click-through -> prioritize that space
  • Light colors photograph larger; dark absorbs space
  • Clutter in photos kills conversions more than in person
  • Window orientation determines optimal photo timing

See photography.md for shot lists and staging checklist.

7. Commercial ROI Framing

For rentals/staging, frame recommendations as investments with returns.

Always quantify when possible:

  • "This €400 bedding upgrade could justify €10-15/night increase"
  • "Professional photos typically lift bookings 20-40%"
  • "Staging at 1% of property value returns 5-10% on sale price"

Don't suggest "nice to have" -> suggest "here's the payback calculation."

Common Traps

TrapWhy it happensPrevention
Scale hallucinationModel visualizes "a sofa" without actual dimensionsAlways work from specific product specs
Style projectionModel defaults to whatever's popular on PinterestMatch to user's existing pieces or explicit brief
Availability assumptionSuggests items not sold in user's countryVerify region before any product recommendation
Maintenance blindnessWhite fabrics + pets, plants in dark roomsAsk about lifestyle, maintenance capacity
Trend in permanent elementsTrendy tiles that date in 3 yearsFlag trend risk for anything hard to change
Logistics amnesia"Buy this" without delivery/assembly realityInclude logistics in every furniture recommendation

平台分布

Local Agent

94.85%
按下载量换算83

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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