add-dataverse

作者: microsoft

将Dataverse表添加到Power Apps代码应用中,并生成TypeScript模型和服务。也可创建新的Dataverse表。用于连接…

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

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

References:

Add Dataverse

Two paths: existing tables (skip to Step 5) or new tables (full workflow).

Workflow

  1. Plan → 2. Setup API Auth → 3. Review Existing Tables → 4. Create Tables → 5. Add Data Source → 6. Review Generated Files → 7. Build

Step 1: Plan

Check memory bank for project context. Ask the user:

  1. Which Dataverse table(s) do they need? (e.g., account, contact, cr123_customentity)
  2. Do the tables already exist in their environment, or do they need to create new ones?

If tables already exist: Skip to Step 5.

If creating new tables:

  • Ask about the data they need and design an appropriate schema
  • Use standard Dataverse tables when appropriate (contact for people, account for organizations)
  • Build a dependency graph -- see data-architecture-reference.md for tier classification
  • Enter plan mode with EnterPlanMode, present ER model with tables, columns, relationships, and creation order
  • Get approval with ExitPlanMode

Step 2: Setup API Auth (if creating tables)

See api-authentication-reference.md for full details.

az account show   # Verify Azure CLI logged in

# Find your Dataverse environment URL:
# In make.powerapps.com → Settings → Developer resources → Web API endpoint
# It looks like: https://<org-name>.crm.dynamics.com/api/data/v9.2/
# Use the base URL: https://<org-name>.crm.dynamics.com

$api = Initialize-DataverseApi -EnvironmentUrl "https://<org>.crm.dynamics.com"
$headers = $api.Headers
$baseUrl = $api.BaseUrl
$publisherPrefix = $api.PublisherPrefix

Requires System Administrator or System Customizer security role.

Step 3: Review Existing Tables (if creating tables)

Always query existing tables first before creating:

$existingTables = Invoke-RestMethod -Uri "$baseUrl/EntityDefinitions?`$filter=IsCustomEntity eq true&`$select=SchemaName,LogicalName,DisplayName" -Headers $headers

See table-management-reference.md for Find-SimilarTables, Compare-TableSchemas, and Build-TableNameMapping functions.

Present findings to user with AskUserQuestion:

  • Tables that can be reused (already exist with matching columns)
  • Tables that need extension (exist but missing columns)
  • Tables that must be created (no match found)

Step 4: Create Tables (if creating tables)

Get explicit confirmation before creating. Create in dependency order:

  • Tier 0: Reference tables (no dependencies)
  • Tier 1: Primary entities (reference Tier 0)
  • Tier 2: Dependent tables (reference Tier 1)

Use safe functions from table-management-reference.md:

Step 5: Add Data Source

For each table:

npx power-apps add-data-source -a dataverse -t <table-logical-name>

Can add multiple tables by running the command for each one.

Step 6: Review Generated Files

The command generates:

  • src/generated/models/{Table}Model.ts -- TypeScript interfaces, plus {Table}FileColumnName, {Table}ImageColumnName, {Table}UploadColumnName union types if the table has file/image columns
  • src/generated/services/{Table}Service.ts -- CRUD methods (create, get, getAll, update, delete) plus upload, downloadFile, downloadImage, deleteFileOrImage if file/image columns exist

Show the user a usage example:

import { AccountsService } from "../generated/services/AccountsService";

const result = await AccountsService.getAll({
  select: ["name", "accountnumber"],
  filter: "statecode eq 0",
  orderBy: ["name asc"],
  top: 50
});
const accounts = result.data || [];

Key rules:

  • Use generated services (e.g., AccountsService.getAll()), not fetch/axios
  • Check result.data for actual data
  • Don't edit generated files unless needed
  • Read dataverse-reference.md before writing any Dataverse code -- picklist fields, virtual fields, lookups, and file/image columns all have critical gotchas

Step 7: Build

npm run build

Fix TypeScript errors before proceeding. Do NOT deploy yet.

Update Memory Bank

Record which tables were added (or created), generated files, and any schema notes.

来自 microsoft 的更多技能

oss-growth
microsoft
OSS增长黑客角色
official
microsoft-foundry
microsoft
端到端部署、评估和管理Foundry代理:Docker构建、ACR推送、托管/提示代理创建、容器启动、批量评估、持续评估、提示优化工作流、agent.yaml、从追踪中整理数据集。用途:将代理部署到Foundry、托管代理、创建代理、调用代理、评估代理、运行批量评估、持续评估、持续监控、持续评估状态、优化提示、改进提示、提示优化器、优化代理指令、改进代理...
officialdevelopmentdevops
azure-ai
microsoft
用于Azure AI:搜索、语音、OpenAI、文档智能。支持搜索、向量/混合搜索、语音转文字、文字转语音、转录、OCR。适用场景:AI搜索、查询搜索、向量搜索、混合搜索、语义搜索、语音转文字、文字转语音、转录、OCR、文字转语音。
officialdevelopmentapi
azure-deploy
microsoft
对已准备好的应用程序执行Azure部署,这些程序需包含现有的.azure/deployment-plan.md和基础设施文件。当用户要求创建新应用程序时,请勿使用此技能——应改用azure-prepare。此技能运行azd up、azd deploy、terraform apply和az deployment命令,并内置错误恢复机制。需要来自azure-prepare的.azure/deployment-plan.md以及来自azure-validate的已验证状态。适用场景:"运行azd up"、"运行azd deploy"、"执行部署"...
officialdevopsaws
azure-storage
microsoft
Azure存储服务,包括Blob存储、文件共享、队列存储、表存储和Data Lake。解答关于存储访问层(热、冷、冷、归档)的问题,说明各层的使用场景及对比。提供对象存储、SMB文件共享、异步消息传递、NoSQL键值存储和大数据分析。包含生命周期管理。用途:Blob存储、文件共享、队列存储、表存储、Data Lake、上传文件、下载Blob、存储账户、访问层等。
officialdevelopmentdatabase
azure-diagnostics
microsoft
使用AppLens、Azure Monitor、资源健康和安全分类调试Azure生产问题。适用场景:调试生产问题、排查应用服务、应用服务CPU过高、应用服务部署失败、排查容器应用、排查函数、排查AKS、kubectl无法连接、kube-system/CoreDNS故障、Pod挂起、CrashLoop、节点未就绪、升级失败、分析日志、KQL、洞察、镜像拉取失败、冷启动问题、健康探测失败……
officialdevopsdevelopment
azure-prepare
microsoft
为Azure应用准备部署(基础设施Bicep/Terraform、azure.yaml、Dockerfile)。用于创建/现代化或创建+部署;不用于跨云迁移(使用azure-cloud-migrate)。请勿用于:copilot-sdk应用(使用azure-hosted-copilot-sdk)。适用场景:"创建应用"、"构建Web应用"、"创建API"、"创建无服务器HTTP API"、"创建前端"、"创建后端"、"构建服务"、"现代化应用"、"更新应用"、"添加身份验证"、"添加缓存"、"托管在Azure上"、"创建并...
officialdevelopmentdevops
azure-validate
microsoft
部署前对Azure就绪状态进行验证。对配置、基础设施(Bicep或Terraform)、RBAC角色分配、托管标识权限及先决条件进行深度检查,然后再部署。适用场景:验证我的应用、检查部署就绪状态、运行预检、验证配置、检查是否可部署、验证azure.yaml、验证Bicep、部署前测试、排查部署错误、验证Azure Functions、验证函数应用、验证无服务器...
officialdevopstesting