v9-component

作者: microsoft

遵循 Fluent UI 模式建立新的 v9 元件,並包含所有必要檔案(hook、styles、render、types、tests、stories、conformance)

npx skills add https://github.com/microsoft/fluentui --skill v9-component

Scaffold a V9 Component

Create a new v9 component named $ARGUMENTS using the repo's Nx generators.

Steps

Adding a component to an existing package

Use the react-component generator:

yarn nx g @fluentui/workspace-plugin:react-component --name $ARGUMENTS --project <project-name>

Where <project-name> is the Nx project (e.g., react-button). This generates all required files: component, types, hook, styles, render, index barrel, and conformance test.

Creating a new package + component

Use the react-library generator first, then add the component:

# Create the package (will prompt for owner team)
yarn create-package

# Or non-interactively:
yarn nx g @fluentui/workspace-plugin:react-library --name <package-name> --owner "<team>"

# Then add the component inside it:
yarn nx g @fluentui/workspace-plugin:react-component --name $ARGUMENTS --project <package-name>

After scaffolding

  1. Review generated files against docs/architecture/component-patterns.md and fill in component-specific logic.

  2. Add styles in use${ARGUMENTS}Styles.styles.ts using design tokens:

    import { makeStyles } from '@griffel/react';
    import { tokens } from '@fluentui/react-theme';
    
  3. Create a default story at the appropriate stories package location if not generated.

  4. Update API docs after adding exports:

    yarn nx run <project>:generate-api
    

Critical Rules

  • Always use ForwardRefComponent with React.forwardRef — never React.FC
  • Always use design tokens from @fluentui/react-theme — never hardcoded colors/spacing/typography
  • Always preserve user className as the LAST argument in mergeClasses()
  • Use _unstable suffix on exported hooks: use$ARGUMENTS_unstable, use${ARGUMENTS}Styles_unstable, render${ARGUMENTS}_unstable
  • Guard any window/document/navigator access with canUseDOM() from @fluentui/react-utilities
  • Do not add dependencies on other Tier 3 component packages (see docs/architecture/layers.md)

Available Generators Reference

GeneratorCommandPurpose
react-componentyarn nx g @fluentui/workspace-plugin:react-componentAdd component to existing package
react-libraryyarn nx g @fluentui/workspace-plugin:react-libraryCreate new v9 package
recipe-generatoryarn nx g @fluentui/workspace-plugin:recipe-generatorCreate a v9 recipe
prepare-initial-releaseyarn nx g @fluentui/workspace-plugin:prepare-initial-releasePrepare package for release (compat/preview/stable)
bundle-size-configurationyarn nx g @fluentui/workspace-plugin:bundle-size-configurationSetup bundle-size tracking
cypress-component-configurationyarn nx g @fluentui/workspace-plugin:cypress-component-configurationSetup Cypress component tests

來自 microsoft 的更多技能

oss-growth
microsoft
開源增長駭客角色
agent-framework-azure-ai-py
microsoft
使用Microsoft Agent Framework Python SDK(agent-framework-azure-ai)构建Azure AI Foundry代理。适用于使用AzureAIAgentsProvider创建持久化代理、使用托管工具(代码解释器、文件搜索、网络搜索)、集成MCP服务器、管理对话线程或实现流式响应。涵盖函数工具、结构化输出和多工具代理。
development
airunway-aks-setup
microsoft
在AKS上設定AI Runway——從裸叢集到執行模型。涵蓋叢集驗證、控制器安裝、GPU評估、供應商設定及首次部署。時機:「設定AI Runway」、「上線AKS叢集」、「安裝AI Runway」、「airunway設定」、「部署模型至AKS」、「在AKS上進行GPU推論」、「在AKS上設定KAITO」、「在AKS上執行LLM」、「在AKS上使用vLLM」、「在AKS上設定模型服務」、「AI Runway控制器」。
devops
appinsights-instrumentation
microsoft
使用Azure Application Insights檢測Web應用程式的指南。提供遙測模式、SDK設定與組態參考。適用時機:如何檢測應用程式、App Insights SDK、遙測模式、什麼是App Insights、Application Insights指南、檢測範例、APM最佳實踐。
devops
applicationinsights-web-ts
microsoft
使用Application Insights JavaScript SDK(@microsoft/applicationinsights-web)為瀏覽器/Web應用程式進行檢測。適用於真實使用者監控(RUM)——頁面檢視、點擊、AJAX/fetch依賴、例外、自訂事件,以及與後端OpenTelemetry追蹤關聯的瀏覽器端GenAI代理追蹤。涵蓋SDK載入器指令碼與npm設定、框架擴充(React、React Native、Angular)、點擊分析、遙測初始化器,以及從瀏覽器發出的代理/工具/模型span的OTel GenAI語意慣例。
devops
azure-ai-anomalydetector-java
microsoft
使用適用於 Java 的 Azure AI 異常偵測器 SDK 建置異常偵測應用程式。在實作單變量/多變量異常偵測、時間序列分析或 AI 驅動監控時使用。
development
azure-ai-language-conversations-py
microsoft
使用 azure-ai-language-conversations Python SDK 實作對話語言理解(CLU)。當使用 ConversationAnalysisClient 分析對話意圖與實體、建置 NLP 功能,或將語言理解整合至應用程式時使用。
development
azure-ai-ml-py
microsoft
Azure Machine Learning SDK v2 for Python。用於機器學習工作區、作業、模型、資料集、計算資源與管線。 觸發詞:「azure-ai-ml」、「MLClient」、「workspace」、「model registry」、「training jobs」、「datasets」。
development