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add-mcscopilot

Adds Microsoft Copilot Studio connector to a Power Apps code app. Use when invoking Copilot Studio agents, sending prompts to agents, or integrating…

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技能内容

📋 Shared Instructions: [shared-instructions.md](${PLUGIN_ROOT}/shared/shared-instructions.md) - Cross-cutting concerns.

Add Microsoft Copilot Studio

Workflow

  1. Check Memory Bank → 2. Add Connector → 3. Configure → 4. Build → 5. Update Memory Bank

Step 1: Check Memory Bank

Check for memory-bank.md per [shared-instructions.md](${PLUGIN_ROOT}/shared/shared-instructions.md).

Step 2: Add Connector

First, find the connection ID (see [connector-reference.md](${PLUGIN_ROOT}/shared/connector-reference.md)):

Run the /list-connections skill. Find the Microsoft Copilot Studio connection 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.

pa app add data-source --connector microsoftcopilotstudio -c <connection-id>

Step 3: Configure

Ask the user which Copilot Studio agent they want to invoke and what operations they need.

Agent Setup Prerequisites (manual steps the user must complete in Copilot Studio):

  1. Publish the agent: In Copilot Studio, click Channels → select Teams → add to Teams → click Publish.
  2. Get the agent name: Under Channels, click "Web app". The connection string URL contains the agent name. Example: https://...api.powerplatform.com/copilotstudio/dataverse-backed/authenticated/bots/cr3e1_myAgent/conversations?... — the agent name is cr3e1_myAgent.

ExecuteCopilotAsyncV2 -- execute an agent and wait for the response:

Use the ExecuteCopilotAsyncV2 operation (path: /proactivecopilot/executeAsyncV2). This is the only endpoint that reliably returns agent responses synchronously. It is the same endpoint used by Power Automate's "Execute Agent and wait" action.

const result = await MicrosoftCopilotStudioService.ExecuteCopilotAsyncV2({
  message: "Your prompt or data here", // Can be a JSON string
  notificationUrl: "https://notificationurlplaceholder" // Required by API but unused; any URL works
});

// Response structure:
// result.responses — Array of response strings from the agent
// result.conversationId — The conversation ID
// result.lastResponse — The last response from the agent
// result.completed — Boolean indicating if the agent finished

Important: Agents often return responses as JSON strings. Parse the responses array to extract meaningful data:

const agentResponse = result.responses?.[0];
if (agentResponse) {
  const parsed = JSON.parse(agentResponse);
  // Extract specific fields, e.g., parsed.trend_summary
}

Use Grep to find specific methods in the generated service file (generated files can be very large — see [connector-reference.md](${PLUGIN_ROOT}/shared/connector-reference.md#inspecting-large-generated-files)).

Known Issues

  • ExecuteCopilot (/execute) -- fire-and-forget, only returns ConversationId, not the actual response. Do NOT use this.
  • ExecuteCopilotAsync (/executeAsync) -- returns 502 "Cannot read server response" errors. Do NOT use this.
  • Conversation turn model (/conversations/{ConversationId}) -- only works after /execute, which doesn't provide responses. Do NOT use this.
  • Response casing varies -- check all variations: conversationId, ConversationId, conversationID.

Step 4: Build

npm run build

Fix TypeScript errors before proceeding. Do NOT deploy yet.

Step 5: Update Memory Bank

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

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本站分层T2
该仓技能数113
原文件路径plugins/code-apps/skills/add-mcscopilot/SKILL.md

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