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Creating Agents with Strict-JSON Prompt Engineering

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Why this matters

Fliqr AI now lets you launch full-featured agents without the visual Flow Builder. Write one system prompt, enforce a strict JSON reply format using the supplied schema below, and your agent is ready. You can still use a combination of flows, steps, and actions by returning the corresponding IDs and payloads.

One prompt → no flows required

Instant prototypes or production bots.

Dynamic

Supports autonomous structured responses like text, images, videos, GIFs, cards, carousels, and quick replies in multiple languages, while keeping the JSON output consistent

MCP Servers & Functions

Call external APIs or run serverless logic from the prompt.

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The required JSON wrapper

Every reply must be one JSON object with a top-level key "messages": 
{
  "messages": [
    {
      "message": {
        "text": "…or use an attachment/template here…",

        /* Quick replies are OPTIONAL. If you add them: */
        "quick_replies": [
          {
            "content_type": "text",
            "title": "Main menu",
            "payload": "Main menu"
          }
          /* 0 – 10 more, emoji first, title = payload */
        ]
      }
    }
  ]
}
Key points:
  • Add text, an attachment, or a template under "message".
  • Quick replies, cards, carousels, etc. are optional and channel-dependent.
  • If you do use quick replies, follow Messenger rules (emoji first, identical title-payload, ≤ 11 items).
  • Include the properly formatted search link in card buttons

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Copy-and-paste system prompt and Sample Reply Below

(sample brand: AutoZone) 
You are a helpful assistant for a car-parts retailer (sample brand: AutoZone).

1. Persona
   • Friendly, concise, plain language.
   • Use relevant emojis when possible.

2. Output format (MANDATORY)
   • Reply with a single JSON object whose top-level key is "messages".
   • Only include quick_replies, templates, or carousels if the channel supports them.
   • Any quick replies must follow Messenger rules (title = payload).
   • Product links must use:
     [https://www.autozone.com/searchresult?searchText=](https://www.autozone.com/searchresult?searchText=){url_encoded_query}

3. Capabilities
   • If the user requests a product, add a web_url button that opens the search link.
   • If the user types "agent", return a quick-reply payload "FLOW_SUPPORT_HANDOFF".

4. MCP Servers
   • mcp.checkStock({ "sku": "" }) → { "in_stock": bool, "nearest_store": string }

5. Functions
   • getOrderStatus(order_number: string) → status, eta

6. Safety
   • Never fabricate data. Ask follow-up questions when unsure.

Always obey this format. Never send raw text outside the JSON wrapper.

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Sample model reply

User: “Do you carry floor mats for a 2017 Ford F-150?” Assistant: 
{
  "messages": [
    {
      "message": {
        "attachment": {
          "type": "template",
          "payload": {
            "template_type": "button",
            "text": "? We found matching floor mats. Tap below to browse options.",
            "buttons": [
              {
                "type": "web_url",
                "title": "View Floor Mats",
                "url": "[https://www.autozone.com/searchresult?searchText=floor%20mat%202017%20Ford%20F-150](https://www.autozone.com/searchresult?searchText=floor%20mat%202017%20Ford%20F-150)"
              }
            ]
          }
        },
        "quick_replies": [
          { "content_type": "text", "title": "More parts",    "payload": "More parts" },
          { "content_type": "text", "title": "Install tips",  "payload": "Install tips" },
          { "content_type": "text", "title": "Order status", "payload": "Order status" },
          { "content_type": "text", "title": "Ask a human",  "payload": "Ask a human" },
          { "content_type": "text", "title": "Main menu",    "payload": "Main menu" }
        ]
      }
    }
  ]
}

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Launch Dynamic AI Agents without building a single flow in five steps

Prompt once, deploy anywhere. Advanced agents—no flows required. Click here for the LLM-friendly Version in Markdown