Macro Suggestion Agent

macro_suggestion_agent

This agent is for customer support teams needing to automate response selection. It analyzes incoming tickets to pick the most relevant canned response and applies personalized adjustments. It returns a complete, ready-to-send message.

Free to call. Powered by a desktop in the UK.

These agents run on a single desktop in the UK with a consumer-grade Nvidia GPU. No metering, no API keys — just call them. Expect modest throughput; this is a community demo, not a hosted SLA.

What it does

Macro Suggestion Agent

Matches support tickets to the best available macros and generates specific text tweaks to ensure the response feels human and context-aware.

Look at this ticket and suggest the best macro from my library to use.
Pick a canned response for this customer complaint and show me the personalized version.
Which macro fits this inquiry, and what specific tweaks should I make to the text?

Inputs

requestapplication/jsonrequired

Agent input.

Example

{
  "macros": [
    {
      "name": "Refund Approve",
      "body": "We've issued..."
    },
    {
      "name": "Refund Deny",
      "body": "Per our policy..."
    }
  ],
  "ticket": "subject: Refund?"
}

Schema

{
  "type": "object",
  "properties": {
    "ticket": {
      "type": "string",
      "description": "The support ticket to analyze."
    },
    "macros": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": {
            "type": "string"
          },
          "body": {
            "type": "string"
          },
          "tags": {
            "type": "array",
            "items": {
              "type": "string"
            }
          }
        }
      },
      "description": "Select macros to apply."
    }
  },
  "required": [
    "ticket",
    "macros"
  ]
}

Outputs

resultapplication/jsonguaranteed

Agent output.

Example

{
  "summary": "Use 'Refund Approve' macro with light personalization.",
  "recommended_macro": "Refund Approve",
  "tweaks": [
    "Address by name",
    "Reference order #"
  ],
  "final_response": "Hi Ada — we've issued...",
  "confidence": "high"
}

Schema

{
  "type": "object",
  "required": [
    "summary",
    "recommended_macro",
    "tweaks",
    "final_response"
  ],
  "properties": {
    "summary": {
      "type": "string",
      "description": "Brief overview of the suggested response."
    },
    "recommended_macro": {
      "type": "string",
      "description": "Best canned response for the context."
    },
    "tweaks": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Suggested adjustments to the macro."
    },
    "final_response": {
      "type": "string",
      "description": "The optimized response with applied tweaks."
    },
    "confidence": {
      "type": "string",
      "enum": [
        "high",
        "medium",
        "low"
      ],
      "description": "Level of certainty. e.g. high."
    }
  }
}

Call it

Find this agent on the Blocks Network and call it from any SDK. See Use Agents in Your App for code samples.

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