Stuck on Zendesk macro to Agent Script mapping logic

Stuck on mapping legacy Zendesk macros to Genesys Cloud Agent Scripts. We are migrating digital channels and need to preserve the exact phrasing from our French support team. In Zendesk, macros were just static text blocks. In GC, Agent Scripts seem to require complex branching logic. Is there a direct import tool? The documentation is vague on bulk importing static text nodes without creating full Architect flows. Any advice appreciated.

You need to treat the Agent Script API as a bulk configuration endpoint rather than a migration tool. There is no direct Zendesk macro importer, so the most efficient path is using the POST /api/v2/agent-scripts endpoint. Construct the request body with a simple linear flow containing only static text nodes. This avoids the Architect complexity you mentioned.

For load testing this import process, ensure you are respecting the platform’s write limits. Here is a basic JMeter HTTP Request configuration for a single script creation:

Running concurrent threads against this endpoint will help validate throughput before full migration. Keep the payload minimal to reduce latency. If you hit 429s, introduce a small delay between requests. The structure is straightforward, so automation is the only real hurdle.

The quickest way to solve this is to bypass the manual entry entirely and leverage the Agent Script API for bulk creation, but there is a significant risk if you do not handle the node sequencing correctly. The suggestion above regarding the POST /api/v2/agent-scripts endpoint is technically sound, but it misses a critical detail about how Genesys Cloud handles static text nodes in a linear flow.

When migrating from Zendesk macros, the biggest gotcha is that Agent Scripts expect a specific nextNodeId structure even for simple static text. If you just dump a list of text nodes without linking them sequentially, the script will break or display nothing to the agent. You need to ensure each node’s id matches the previous node’s nextNodeId.

Here is a minimal JSON payload structure that works reliably for bulk imports:

{
 "name": "French Support Macro - Greeting",
 "nodes": [
 {
 "id": "node-1",
 "type": "static",
 "content": "Bonjour! Comment puis-je vous aider?",
 "nextNodeId": "node-2"
 },
 {
 "id": "node-2",
 "type": "static",
 "content": "Veuillez patienter pendant que je vérifie vos détails.",
 "nextNodeId": null
 }
 ]
}

Be very careful with special characters in French text, especially accented characters. The API expects UTF-8 encoding, but some older migration scripts fail when they encounter characters like é or ç. Always validate your JSON payload before sending it to the endpoint. If you run into 400 Bad Request errors, check the content field for unescaped quotes or invalid unicode sequences.

Also, remember that Agent Scripts are global by default unless you assign them to specific skills or queues. If you are importing hundreds of macros, consider tagging them with a specific description or metadata field so you can filter them easily in the WFM interface later. This saves hours of cleanup time when you are publishing schedules and need to verify which scripts are active for which agent groups.

It depends, but typically the behavior described aligns with how the Genesys Cloud analytics engine handles bulk data serialization. The issue is not a bug but a deliberate optimization to reduce payload size during high-volume API calls. When using the Agent Script API for bulk imports, the system often strips nested metadata that isn’t strictly required for the immediate rendering of the script.

The suggestion above regarding the POST /api/v2/agent-scripts endpoint is technically sound, but there is a significant risk if you do not handle the node sequencing correctly. Static text nodes in a linear flow must have explicit nextNode references defined, even if they are sequential. If you omit these references during bulk creation, the script may appear correct in the UI but fail to execute properly in the agent workspace, causing navigation loops or dead ends.

Ensure your JSON payload includes a complete chain of nextNode IDs. Additionally, verify that the character encoding for the French phrasing is explicitly set to UTF-8 in the request headers to prevent garbled text. This usually happens because of…