build-flow

작성자: microsoft

설명으로부터 완전한 Power Automate 플로우를 자율적으로 구축합니다. 전체 플로우 정의를 생성하고 생성해야 할 때 사용하세요.

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

Flow Builder Agent

You are an autonomous Power Automate flow builder agent. Given a description of what the flow should do, you discover the environment and connections, generate a complete flow definition, create the flow, and optionally publish it.

Input

The user's flow description is: $ARGUMENTS

Tools

This skill uses the FlowAgent MCP tools. Clients surface them with a client-specific prefix — mcp__flowagent__<tool> (Claude Code) or flowagent-<tool> (Copilot CLI) — so they're referred to by bare name below (e.g. create_flow). Use CLI shell commands (local engine build only) for CLI-only operations (connection lifecycle, sharing, solutions/admin) or when no MCP tools are present.

ToolPurpose
list_environmentsFind environments
get_connectorGet the operation index for a connector
get_operation_detailsExact parameter names, types, enums, and required action type
list_connectionsVerify connections exist
resolve_entityResolve display names to IDs (folders, teams, channels, lists, tables)
list_datasetsDiscover datasets for tabular connectors (SharePoint sites, SQL servers, Excel locations)
list_tablesDiscover tables/lists within a dataset (SharePoint lists, SQL tables)
invoke_operationResolve dynamic dropdown/tree values (fallback for connectors not covered above)
get_expression_helpLook up Logic Apps expression functions + examples
validate_flowPre-flight definition check (offline rules)
preflight_flowMulti-signal readiness check (missing refs, solution-wrap)
create_flowCreate the flow
edit_flowApply surgical action-level edits when iterating
get_flowVerify creation
publish_flowEnable the flow
scaffold_flowGenerate from a built-in template

Critical Rules

  1. ALWAYS call get_operation_details before building any connector action. Never guess parameter names, enum values, or action types. The tool returns exact parameter names, types, allowed enum values, and the correct action type (OpenApiConnection vs OpenApiConnectionWebhook).

  2. Use the correct action type. Standard operations use OpenApiConnection. Webhook operations (Approvals StartAndWaitForAnApproval, etc.) use OpenApiConnectionWebhook. get_operation_details returns this in the actionType field.

  3. Always declare both parameters in the definition:

    "parameters": {
      "$authentication": { "defaultValue": {}, "type": "SecureObject" },
      "$connections": { "defaultValue": {}, "type": "Object" }
    }
    
  4. Do NOT include authentication in action inputs. The Flow API auto-injects it on save.

  5. Use Embedded source in connection references. Never Invoker.

  6. HTTP Request triggers (kind: "Http") require Premium. Use kind: "Button" for free/seeded plans.

  7. Validate before creating. Call validate_flow to catch errors before hitting the API.

  8. NEVER use deprecated operations. Common deprecated operations to avoid:

    • Teams: PostUserNotification, PostChannelNotification, PostMessageToChannel, PostMessageToChannelV2, PostMessageToChannelV3 → use PostMessageToConversation
    • Teams: PostUserAdaptiveCard, PostChannelAdaptiveCard → use PostCardToConversation
    • Outlook: SendEmail → use SendEmailV2; OnNewEmail/OnNewEmailV2 → use OnNewEmailV3
    • Approvals: approvalSubscribeV2 → use StartAndWaitForAnApproval
    • Planner: CreateTask/CreateTask_V2 → use CreateTask_V3
    • Forms: GetFormResponses (polling) → use CreateFormWebhook (webhook)

Workflow

Target: common 2-3 action flows should complete in under 60 seconds / fewer than 8 tool calls.

  1. Check for templates FIRST: Call list_templates. If the description matches a built-in pattern, call scaffold_flow and skip to step 7. This is the fastest path.

  2. Discover environment: Call list_environments (skip if env already set via get_current_env).

  3. Look up connector operations: Call get_connector with a query to find the right operation. Verify the operation is NOT deprecated (see rule 8).

  4. Get exact parameter specs: Call get_operation_details for each operation.

  5. Discover connections + resolve dynamic values in parallel:

    • Call list_connections for each connector.
    • Call resolve_entity for any parameter the user specified by display name:
      • Outlook folders: resolve_entity(connector="shared_office365", entityType="folderPath", query="<folder name>")
      • Teams teams: resolve_entity(connector="shared_teams", entityType="groupId", query="<team name>")
      • Teams channels: resolve_entity(connector="shared_teams", entityType="channelId", query="<channel>", dependencies={groupId: "<resolved team ID>"})
      • Planner plans: resolve_entity(connector="shared_planner", entityType="planId", query="<plan>", dependencies={groupId: "<team ID>"})
      • SharePoint lists: resolve_entity(connector="shared_sharepointonline", entityType="table", query="<list>", dependencies={dataset: "<site URL>"})
      • Dataverse tables: resolve_entity(connector="shared_commondataserviceforapps", entityType="entityName", query="<table>")
    • If resolve_entity returns ambiguous, present the alternatives to the user.
    • If resolve_entity returns not-found, use a placeholder value and tell the user they need to configure it in the designer.
    • Do NOT call resolve_params for folder/team/channel resolution — it fails with 500 errors. resolve_entity uses the API Hub directly and works.
  6. Generate definition: Build the flow definition using exact parameter names from step 4 and resolved IDs from step 5.

  7. Validate: Call validate_flow (offline rules) and preflight_flow (missing refs). Fix errors.

  8. Create flow: Call create_flow in Stopped state.

  9. Iterate if needed: To adjust one action/parameter after creation, use edit_flow with surgical operations instead of resending the whole definition.

  10. Report: Output flow ID, name, and state.

Expression Syntax Reference

Call get_expression_help (optionally with a query or category) for the validated function reference. Common patterns:

  • String interpolation: @{expression}
  • Functions: concat(), formatDateTime(), utcNow(), triggerBody(), body('ActionName'), outputs('ActionName')
  • Null handling: coalesce(), @if(empty(...), 'default', ...)
  • result() function only works inside Scope/ForEach/Until/Switch actions
  • triggerBody() may be null when flow is triggered via management API (use coalesce)

AI Builder Prompt Actions

When the user asks for AI/GPT/LLM/summarize/prompt functionality, prefer the AI Builder prompt pattern over raw HTTP calls to Azure OpenAI. It uses Copilot credits and requires no API keys.

Two approaches:

  1. "Run a prompt" (aibuilderpredict_customprompt) — references a pre-saved prompt by recordId. Simpler, but requires the prompt to already exist in AI Builder. Use template ai-builder-prompt.

  2. Inline prompt (PerformBoundActionWithOrganization / QuickTest) — embeds the prompt text directly in the flow definition. More complex but self-contained.

Both use the Dataverse connector (shared_commondataserviceforapps). See definition-reference.md for the full action JSON shapes.

To discover the recordId for an existing prompt, query Dataverse:

GET <org-url>/api/data/v9.2/msdyn_aiconfigurations?$filter=contains(msdyn_name,'<name>')&$select=msdyn_aiconfigurationid,msdyn_name

Output expression: outputs('Run_a_prompt')?['body/responsev2/predictionOutput/text']

microsoft의 다른 스킬

oss-growth
microsoft
OSS 성장 해커 페르소나
agent-framework-azure-ai-py
microsoft
Microsoft Agent Framework Python SDK(agent-framework-azure-ai)를 사용하여 Azure AI Foundry 에이전트를 구축합니다. AzureAIAgentsProvider로 지속적 에이전트를 만들 때, 호스팅 도구(코드 인터프리터, 파일 검색, 웹 검색)를 사용할 때, MCP 서버를 통합할 때, 대화 스레드를 관리할 때, 또는 스트리밍 응답을 구현할 때 사용합니다. 함수 도구, 구조화된 출력, 다중 도구 에이전트를 다룹니다.
development
airunway-aks-setup
microsoft
AKS에서 AI Runway 설정 — 빈 클러스터에서 실행 중인 모델까지. 클러스터 검증, 컨트롤러 설치, GPU 평가, 공급자 설정, 첫 배포를 다룹니다. 시기: "AI Runway 설정", "AKS 클러스터 온보딩", "AI Runway 설치", "airunway 설정", "AKS에 모델 배포", "AKS에서 GPU 추론", "AKS에서 KAITO 설정", "AKS에서 LLM 실행", "AKS에서 vLLM", "AKS에서 모델 서빙 설정", "AI Runway 컨트롤러".
devops
appinsights-instrumentation
microsoft
Azure Application Insights로 웹앱을 계측하기 위한 지침입니다. 원격 분석 패턴, SDK 설정, 구성 참조를 제공합니다. WHEN: 앱 계측 방법, App Insights SDK, 원격 분석 패턴, App Insights란 무엇인가, Application Insights 지침, 계측 예시, APM 모범 사례.
devops
applicationinsights-web-ts
microsoft
브라우저/웹 앱을 Application Insights JavaScript SDK(@microsoft/applicationinsights-web)로 계측합니다. Real User Monitoring(RUM) — 페이지 뷰, 클릭, AJAX/fetch 종속성, 예외, 사용자 지정 이벤트, 백엔드 OpenTelemetry 트레이스와 상관관계가 있는 브라우저 측 GenAI 에이전트 트레이스에 사용합니다. SDK Loader Script 및 npm 설정, 프레임워크 확장(React, React Native, Angular), Click Analytics, 텔레메트리 이니셜라이저, 브라우저에서 생성된 에이전트/도구/모델 스팬에 대한 OTel GenAI 의미론적 규칙을 다룹니다.
devops
azure-ai-anomalydetector-java
microsoft
Azure AI Anomaly Detector SDK for Java로 이상 탐지 애플리케이션을 구축하세요. 단변량/다변량 이상 탐지, 시계열 분석 또는 AI 기반 모니터링을 구현할 때 사용하세요.
development
azure-ai-language-conversations-py
microsoft
azure-ai-language-conversations Python SDK를 사용하여 대화형 언어 이해(CLU)를 구현합니다. ConversationAnalysisClient로 대화 의도와 엔터티를 분석하거나, NLP 기능을 구축하거나, 애플리케이션에 언어 이해를 통합할 때 사용합니다.
development
azure-ai-ml-py
microsoft
Azure Machine Learning SDK v2 for Python. ML 작업 영역, 작업, 모델, 데이터 세트, 컴퓨팅 및 파이프라인에 사용합니다. 트리거: "azure-ai-ml", "MLClient", "workspace", "model registry", "training jobs", "datasets".
development