edit-triggers

Edit Topic Triggers

Modify how a topic gets triggered: trigger phrases (triggerQueries) and model description (modelDescription).

Instructions

1. Auto-discover the agent directory:

   Glob: **/agent.mcs.yml
   

   NEVER hardcode an agent name.

2. Find the target topic:

   Glob: <agent-dir>/topics/*.topic.mcs.yml
   

   If $ARGUMENTS specifies a topic name, match it. Otherwise, list all topics and ask which one.

3. Read the topic file and identify what to change.

4. Check the agent's settings.mcs.yml for GenerativeActionsEnabled. This determines which trigger mechanism matters most.

5. Make the requested changes using the Edit tool.

Model Description (modelDescription)

The modelDescription is a natural language description at the root of an AdaptiveDialog that tells the generative orchestrator when to route to this topic. When GenerativeActionsEnabled: true, this is the primary way the agent decides which topic to trigger — even more important than trigger phrases.

kind: AdaptiveDialog
modelDescription: This topic helps users order a pizza by collecting their preferred size, toppings, and delivery address.
beginDialog:
  kind: OnRecognizedIntent
  id: main
  ...

Best Practices for Model Description

• Write a clear, specific sentence describing what the topic does and when it should be used
• Focus on the user's intent: "Use this topic when the user asks for information about our perfumes" rather than "This topic sends a message"
• Include key scenarios the topic covers: "This topic handles billing inquiries, refund requests, and payment issues"
• Keep it concise but complete — the orchestrator reads this to decide routing
• Avoid vague descriptions like "This topic handles requests" — be specific about which requests

Examples from Real Topics

# Good — specific about what the topic does and when to use it
modelDescription: Use this topic when the user asks for help or needs assistance with something. Search the SharePoint knowledge base to find relevant information.

# Good — describes the full flow
modelDescription: This topic takes the user's favorite color, generates a word by concatenating the color with four random digits, and returns the generated word. If the color is white, it also provides information about the wavelength.

# Good — describes the computation
modelDescription: This sample topic performs the sum between the two numbers in input