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Agent Skill · 运维和基础设施

product-modeling(product modeling 命令行)

product-modeling 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

product-modeling 是运维和基础设施类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在运维和基础设施类的 2,449 个 Skill 里排第 2,289。

总安装 216周安装 9GitHub Stars 28下载 72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:product-modeling(product modeling 命令行)
来源仓库:https://github.com/saleor/configurator
仓库路径:skills/product-modeling
安装命令:
npx skills add https://github.com/saleor/configurator --skill product-modeling
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/saleor/configurator --skill product-modeling

这个 Skill 是做什么的

运维和基础设施类 Skill 处理部署、监控、日志和云资源,多数需要较高的执行权限。

product-modeling 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中围绕项目结构、代码演进或协作流程进行建模分析。

它支持产品架构与技术选型的决策辅助,可用于微服务拆分、数据流设计与依赖关系梳理等场景。通过 npx skills add https://github.com/saleor/configurator --skill product-modeling 安装,应确认 Saleor 版本兼容性。

注意该技能可能解析复杂目录结构,避免误读配置文件导致错误推断。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/product-modeling

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/saleor/configurator --skill product-modeling;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

product-modeling 怎么安装?

在终端执行 npx skills add https://github.com/saleor/configurator --skill product-modeling。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

product-modeling 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。

product-modeling 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。

product-modeling 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。

product-modeling 用的人多吗?

公开数据是累计安装 216 次,近一周安装 9 次,下载 72 次,GitHub 28 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。

product-modeling 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。
  • 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。
  • 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。
  • 需要处理运维和基础设施类任务、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。
  • 需要厂商级技术支持和 SLA 的生产系统。

运维和基础设施类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
brainstorming

头脑风暴 · Codex、Claude

3,148,776173,131操作浏览器MIT通过
copywriting

文案写作 · Codex、Claude

1,996,72425,583需要联网MIT通过
openclaw-secure-linux-cloud

OpenClaw secure linux cloud 命令行 · Codex、Claude

1,853,08840接触敏感数据未明确未通过
xget

xget 命令行 · Codex、Claude

1,799,28040执行命令未明确未通过
requesting-code-review

代码审查请求 · Codex、Claude

1,590,144173,103权限未标注MIT通过
product-modeling

product modeling 命令行 · 本页

21628只读未明确通过

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

Saleor Domain Modeling

Overview

This skill helps you design your product catalog structure in Saleor -- choosing the right product types, attributes, variants, categories, and collections. The key decisions are what makes a product vs. a variant, and which attribute type to use for each field.

When to Use

  • "How do I model my products?"
  • "What attributes should I use?"
  • "Product vs variant attributes?"
  • "When to use DROPDOWN vs MULTISELECT?"
  • "How to structure my product types?"
  • "Categories vs Collections?"
  • "When to use Models (Pages) vs Attributes?"
  • When NOT looking for YAML syntax -- use configurator-schema instead
  • When NOT looking for CLI commands -- use configurator-cli instead

The Core Flow

This is the most important relationship to understand:

1. ATTRIBUTES (define fields)
   └── Reusable typed fields: Size (DROPDOWN), Color (SWATCH), Brand (DROPDOWN)

2. PRODUCT TYPES (define structure)
   └── Assign attributes:
       ├── productAttributes: Brand, Material (same for all variants)
       └── variantAttributes: Size, Color (create SKU combinations)

3. PRODUCTS (create items)
   └── Instance of a ProductType:
       ├── Set values: Brand="Nike", Material="Cotton"
       └── Define variants with SKU combinations

4. VARIANTS (purchasable SKUs)
   └── Each combination = 1 variant:
       ├── SKU: "TSHIRT-BLK-M" -> Size="M", Color="Black", Price=$29.99
       └── SKU: "TSHIRT-WHT-L" -> Size="L", Color="White", Price=$29.99

Key insight: Attributes are building blocks. ProductTypes assemble them into templates. Products are instances. Variants are what customers buy.

Decision Framework: Product vs Variant Attributes

This is the most critical modeling decision.

Use Product-Level When:

QuestionIf YES, use Product Level
Same value for all sizes/colors?Brand, Material, Manufacturer
Descriptive information?Care Instructions, Specs
For filtering/categorization only?Style, Gender, Season

Use Variant-Level When:

QuestionIf YES, use Variant Level
Creates a separate purchasable item?Size, Color, Storage
Affects price?Size (XL costs more), quality tier
Needs separate inventory tracking?Each size needs its own stock
Customer selects this at checkout?Color picker, size selector

Quick Decision Matrix

AttributeProductVariantWhy
BrandxSame for all variants
SizexCreates separate SKUs
ColorxCreates separate SKUs
MaterialxUsually same for product
Storage (64GB/128GB)xDifferent prices
Care InstructionsxSame for all variants
WeightxMay differ per size

Attribute Type Selection

Saleor supports 12 attribute input types. Use this decision tree:

Is it a CHOICE from predefined options?
├── YES: Can user select MULTIPLE?
│   ├── YES -> MULTISELECT
│   └── NO: Is it a COLOR/PATTERN?
│       ├── YES -> SWATCH
│       └── NO: Is it YES/NO?
│           ├── YES -> BOOLEAN
│           └── NO -> DROPDOWN
└── NO: Is it a NUMBER with units?
    ├── YES -> NUMERIC
    └── NO: Is it a DATE?
        ├── YES -> DATE (or DATE_TIME if time needed)
        └── NO: Is it long formatted text?
            ├── YES -> RICH_TEXT
            └── NO: Is it a file/document?
                ├── YES -> FILE
                └── NO: Link to another entity?
                    ├── YES -> REFERENCE
                    └── NO -> PLAIN_TEXT

For the complete attribute type reference, see references/attribute-types-deep-dive.md.

Variant Matrix Planning

Before creating variants, calculate the SKU explosion:

SKU Count = Value1 x Value2 x Value3 x ...

Example: T-Shirt
- Sizes: XS, S, M, L, XL, XXL (6)
- Colors: Black, White, Navy, Gray, Red (5)
- SKUs: 6 x 5 = 30 variants per product
SKU CountAssessmentRecommendation
1-10ManageableGood for most products
11-50ModerateFine for fashion, needs inventory planning
51-100HighConsider splitting into multiple products
100+Too manySimplify -- move some attributes to product level

Tips for high counts: Split by product line, reduce dimensions, move non-purchasable attributes to product level.

Industry Patterns

Quick reference for common store types:

PatternProduct-Level AttrsVariant-Level AttrsTypical SKUs
ApparelBrand, Material, CareSize, Color30/product
ElectronicsBrand, Screen, Processor, FeaturesStorage, Color20/product
FurnitureBrand, Style, Capacity, DimensionsFabric, Color16/product
Food & BeverageOrigin, Roast, Flavor, CertificationsSize, Grind12/product
Digital ProductsPublisher, Platform, FeaturesLicense Type, Duration9/product

For complete YAML examples of each pattern, see references/industry-patterns.md.

Categories vs Collections

Both organize products, but they serve different purposes:

AspectCategoryCollection
StructureHierarchical (tree)Flat (list)
Assignment1 product = 1 category1 product = many collections
PurposeTaxonomy, navigationMerchandising, promotions
ExamplesElectronics > Phones > Smartphones"Summer Sale", "New Arrivals"

Use Categories for main site navigation, browse/filter structure, SEO URLs. Use Collections for curated groups, promotions, campaigns, temporary groupings.

Keep category trees to 3 levels deep. If you need a 4th level, consider using Collections instead.

Models and Structures

Models (Pages/PageTypes) let you create custom entities beyond products -- like Brands, Ingredients, or Scent Profiles. Use them when data is shared across many products, has its own attributes, and needs its own page.

Structures (Menus) assemble Categories, Collections, Models, and URLs into navigation hierarchies.

For complete guidance and examples, see references/models-and-structures.md.

Workflow: Designing a New Product Type

  1. List all product characteristics -- write down every field/attribute
  2. Categorize each -- apply the decision framework (product vs variant)
  3. Select types -- use the attribute type decision tree
  4. Calculate SKU count -- ensure the variant matrix is manageable
  5. Write the YAML -- create the ProductType configuration
  6. Validate -- deploy with --plan to check structure

Common Mistakes

MistakeFix
Over-dimensioning variants (6 sizes x 10 colors x 4 materials = 240 SKUs)Move non-purchasable attributes to product level. Aim for under 50 SKUs.
Using variant attributes for non-inventory fieldsIf it doesn't create a separate SKU (like Care Instructions), it's a product attribute
Product attributes that should varyIf value differs by size (e.g., Weight), move to variant level
Too many product typesReuse types when products share the same attribute structure
Skipping variant planningAlways calculate SKU count before creating product types

Additional Resources

Reference Files

Related Skills

  • configurator-schema - Complete YAML schema reference
  • saleor-domain - Entity relationships and Saleor concepts
  • configurator-recipes - Complete store templates

平台分布

Codex

34.23%
按下载量换算25

Claude

30.75%
按下载量换算22

Cursor

19.37%
按下载量换算14

Gemini CLI

8.99%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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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