M365 Agents Ts
M365 Agents Ts is an code AI skill with a core value of |. It
helps developers solve real-world problems in the code domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
|
Quick Facts
mkdir -p ./skills/m365-agents-ts && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/m365-agents-ts/SKILL.md -o ./skills/m365-agents-ts/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Microsoft 365 Agents SDK (TypeScript)
Build enterprise agents for Microsoft 365, Teams, and Copilot Studio using the Microsoft 365 Agents SDK with Express hosting, AgentApplication routing, streaming responses, and Copilot Studio client integrations.
Before implementation
- Use the microsoft-docs MCP to verify the latest API signatures for AgentApplication, startServer, and CopilotStudioClient.
- Confirm package versions on npm before wiring up samples or templates.
Installation
npm install @microsoft/agents-hosting @microsoft/agents-hosting-express @microsoft/agents-activity
npm install @microsoft/agents-copilotstudio-clientEnvironment Variables
PORT=3978
AZURE_RESOURCE_NAME=<azure-openai-resource>
AZURE_API_KEY=<azure-openai-key>
AZURE_OPENAI_DEPLOYMENT_NAME=gpt-4o-mini
TENANT_ID=<tenant-id>
CLIENT_ID=<client-id>
CLIENT_SECRET=<client-secret>
COPILOT_ENVIRONMENT_ID=<environment-id>
COPILOT_SCHEMA_NAME=<schema-name>
COPILOT_CLIENT_ID=<copilot-app-client-id>
COPILOT_BEARER_TOKEN=<copilot-jwt>Core Workflow: Express-hosted AgentApplication
import { AgentApplication, TurnContext, TurnState } from "@microsoft/agents-hosting";
import { startServer } from "@microsoft/agents-hosting-express";
const agent = new AgentApplication<TurnState>();
agent.onConversationUpdate("membersAdded", async (context: TurnContext) => {
await context.sendActivity("Welcome to the agent.");
});
agent.onMessage("hello", async (context: TurnContext) => {
await context.sendActivity(`Echo: ${context.activity.text}`);
});
startServer(agent);Streaming responses with Azure OpenAI
import { azure } from "@ai-sdk/azure";
import { AgentApplication, TurnContext, TurnState } from "@microsoft/agents-hosting";
import { startServer } from "@microsoft/agents-hosting-express";
import { streamText } from "ai";
const agent = new AgentApplication<TurnState>();
agent.onMessage("poem", async (context: TurnContext) => {
context.streamingResponse.setFeedbackLoop(true);
context.streamingResponse.setGeneratedByAILabel(true);
context.streamingResponse.setSensitivityLabel({
type: "https://schema.org/Message",
"@type": "CreativeWork",
name: "Internal",
});
await context.streamingResponse.queueInformativeUpdate("starting a poem...");
const { fullStream } = streamText({
model: azure(process.env.AZURE_OPENAI_DEPLOYMENT_NAME || "gpt-4o-mini"),
system: "You are a creative assistant.",
prompt: "Write a poem about Apollo.",
});
try {
for await (const part of fullStream) {
if (part.type === "text-delta" && part.text.length > 0) {
await context.streamingResponse.queueTextChunk(part.text);
}
if (part.type === "error") {
throw new Error(`Streaming error: ${part.error}`);
}
}
} finally {
await context.streamingResponse.endStream();
}
});
startServer(agent);Invoke activity handling
import { Activity, ActivityTypes } from "@microsoft/agents-activity";
import { AgentApplication, TurnContext, TurnState } from "@microsoft/agents-hosting";
const agent = new AgentApplication<TurnState>();
agent.onActivity("invoke", async (context: TurnContext) => {
const invokeResponse = Activity.fromObject({
type: ActivityTypes.InvokeResponse,
value: { status: 200 },
});
await context.sendActivity(invokeResponse);
await context.sendActivity("Thanks for submitting your feedback.");
});Copilot Studio client (Direct to Engine)
import { CopilotStudioClient } from "@microsoft/agents-copilotstudio-client";
const settings = {
environmentId: process.env.COPILOT_ENVIRONMENT_ID!,
schemaName: process.env.COPILOT_SCHEMA_NAME!,
clientId: process.env.COPILOT_CLIENT_ID!,
};
const tokenProvider = async (): Promise<string> => {
return process.env.COPILOT_BEARER_TOKEN!;
};
const client = new CopilotStudioClient(settings, tokenProvider);
const conversation = await cl🎯 Best For
- Claude users
- Software engineers
- Development teams
- Tech leads
💡 Use Cases
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply M365 Agents Ts to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Is M365 Agents Ts compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for M365 Agents Ts?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install M365 Agents Ts?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/m365-agents-ts/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.