add-connector

作者: microsoft

将任意Power Platform连接器添加到Power Apps代码应用中。适用于未被特定技能覆盖的连接器的通用后备方案。

npx skills add https://github.com/microsoft/power-platform-skills --skill add-connector

📋 Shared Instructions: shared-instructions.md - Cross-cutting concerns.

Add Connector (Generic)

Fallback skill for any connector not covered by a specific /add-* skill. For common connectors, prefer the dedicated skills:

  • /add-dataverse -- Dataverse tables
  • /add-azuredevops -- Azure DevOps
  • /add-teams -- Microsoft Teams
  • /add-excel -- Excel Online (Business)
  • /add-onedrive -- OneDrive for Business
  • /add-sharepoint -- SharePoint Online
  • /add-office365 -- Office 365 Outlook (calendar, email, contacts)
  • /add-workiq -- Work IQ (M365 Copilot Search)

Workflow

  1. Check Memory Bank → 2. Identify Connector → 3. Add Connector → 4. Inspect & Configure → 5. Build → 6. Update Memory Bank

Step 1: Check Memory Bank

Check for memory-bank.md per shared-instructions.md.

Step 2: Identify Connector

If $ARGUMENTS is provided or the caller already specified the connector, use it directly and skip the question below.

Otherwise, ask the user which connector they want to add. Browse available connectors: Connector Reference

Before proceeding, check if the connector has a dedicated skill. If it does, delegate immediately and STOP:

Connector API nameDelegate to
shared_a365copilotchatmcp/add-workiq
sharepointonline/add-sharepoint
teams/add-teams
excelonlinebusiness/add-excel
onedriveforbusiness/add-onedrive
azuredevops/add-azuredevops
office365/add-office365
commondataservice/add-dataverse

Invoke the appropriate skill with the same $ARGUMENTS and do not continue this skill's workflow.

Common connector API names:

  • sharepointonline, teams, excelonlinebusiness, onedriveforbusiness
  • azuredevops, azureblob, azurequeues
  • office365, office365users, office365groups
  • sql, commondataservice

Step 3: Add Connector

First, find the connection ID (see connector-reference.md):

Run the /list-connections skill. Find the connector in the output. If none exists, direct the user to create one using the environment-specific Connections URL — construct it from the active environment ID in context (from power.config.json or a prior step): https://make.powerapps.com/environments/<environment-id>/connections → + New connection → search for the connector → Create.

# Non-tabular connectors (Teams, Azure DevOps, etc.)
pa app add data-source --connector <connector-api-name> -c <connection-id>

# Tabular connectors (SharePoint, Excel, SQL, etc.) -- also need dataset and table
pa app add data-source --connector <connector-api-name> -c <connection-id> -d '<dataset>' --table '<table>'

Parameter reference:

  • --connector (apiId) -- connector name (e.g., sharepointonline, teams). On the flat power-apps binary this is --api-id/-a.
  • -c (connectionId) -- required for all non-Dataverse connectors. Get from /list-connections.
  • -d (dataset) -- required for tabular datasources (e.g., SharePoint site URL, SQL database). Not needed for Dataverse.
  • --table (table) -- table/list name for tabular datasources (e.g., SharePoint list, Dataverse table logical name). On the flat power-apps binary this is --resource-name/-t.

Step 4: Inspect & Configure

After adding, inspect the generated files. Generated service files can be very large -- use Grep to find specific methods instead of reading the entire file:

Grep pattern="async \w+" path="src/generated/services/<Connector>Service.ts"

Files to check:

  • src/generated/services/<Connector>Service.ts -- available operations and their parameters
  • src/generated/models/<Connector>Model.ts -- TypeScript interfaces (if generated)
  • .power/schemas/<connector>/ -- connector schema and configuration

For each method the user needs:

  1. Grep for the method name to find its signature
  2. Read just that method's section (use offset and limit parameters on Read)
  3. Identify required vs optional parameters and response type

Help the user write code using the generated service methods.

Step 5: Build

npm run build

Fix TypeScript errors before proceeding. Do NOT deploy yet.

Step 6: Update Memory Bank

Update memory-bank.md with: connector added, configured operations, build status.

来自 microsoft 的更多技能

oss-growth
microsoft
OSS增长黑客角色
agent-framework-azure-ai-py
microsoft
使用Microsoft Agent Framework Python SDK(agent-framework-azure-ai)构建Azure AI Foundry代理。在创建使用AzureAIAgentsProvider的持久化代理、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时使用。涵盖函数工具、结构化输出和多工具代理。
development
airunway-aks-setup
microsoft
在AKS上设置AI Runway——从裸集群到运行模型。涵盖集群验证、控制器安装、GPU评估、提供商设置和首次部署。适用场景:“设置AI Runway”、“接入AKS集群”、“安装AI Runway”、“airunway设置”、“将模型部署到AKS”、“在AKS上进行GPU推理”、“在AKS上配置KAITO”、“在AKS上运行LLM”、“在AKS上使用vLLM”、“在AKS上设置模型服务”、“AI Runway控制器”。
devops
appinsights-instrumentation
microsoft
使用Azure Application Insights对Web应用进行插桩的指南。提供遥测模式、SDK设置和配置参考。适用场景:如何对应用进行插桩、App Insights SDK、遥测模式、什么是App Insights、Application Insights指南、插桩示例、APM最佳实践。
devops
applicationinsights-web-ts
microsoft
使用Application Insights JavaScript SDK(@microsoft/applicationinsights-web)为浏览器/Web应用添加检测。用于真实用户监控(RUM)——页面视图、点击、AJAX/fetch依赖项、异常、自定义事件,以及与后端OpenTelemetry追踪关联的浏览器端GenAI代理追踪。涵盖SDK加载器脚本和npm设置、框架扩展(React、React Native、Angular)、点击分析、遥测初始化器,以及从浏览器发出的代理/工具/模型跨度所遵循的OTel GenAI语义约定。
devops
azure-ai-anomalydetector-java
microsoft
使用适用于 Java 的 Azure AI 异常检测器 SDK 构建异常检测应用程序。在实现单变量/多变量异常检测、时间序列分析或 AI 驱动的监控时使用。
development
azure-ai-language-conversations-py
microsoft
使用azure-ai-language-conversations Python SDK实现对话语言理解(CLU)。当使用ConversationAnalysisClient分析对话意图和实体、构建NLP功能或将语言理解集成到应用程序中时使用。
development
azure-ai-ml-py
microsoft
Azure Machine Learning SDK v2 for Python。用于机器学习工作区、作业、模型、数据集、计算资源和管道。 触发词:“azure-ai-ml”、“MLClient”、“工作区”、“模型注册表”、“训练作业”、“数据集”。
development