How do I correctly to prevent an agent from closing a conversation if mandatory script steps remain unchecked in the Architect flow?
The current configuration allows immediate closure, bypassing compliance requirements in the Europe/Paris region. Need a reliable validation method within the flow logic rather than relying on manual agent adherence.
To enforce script completion, inject a Data Action in the flow that queries the conversation metadata for specific script step statuses before the “Close Conversation” node. The Data Action should return a boolean based on whether all required steps have a completed status. Route the flow through a decision node that checks this boolean; if false, loop back to the script interaction block or trigger a warning message to the agent. This ensures the flow logic itself acts as the gatekeeper, independent of manual agent actions.
This approach leverages the platform’s state management rather than relying on external compliance tools. Ensure the script steps are configured to update their status immediately upon interaction, as delayed updates can cause false negatives in the validation logic. For high-volume environments, cache the script status in a temporary variable to reduce API calls during the final validation check. This pattern is standard for regulated markets requiring strict adherence tracking.
be careful with that loop. if the data action times out, the agent gets stuck in an infinite retry cycle. seen this break digital channels in london. better to use a timer node with a fallback to supervisor escalation instead of a hard block. also, check the version tag on the script update to avoid optimistic locking errors.
Check your JMeter thread group settings before implementing that loop logic. While the data action approach is sound for validation, adding synchronous API calls inside a tight loop during peak hours can quickly hit the platform API rate limits, especially in ap-southeast-1 where latency varies. I observed similar 429 errors when testing concurrent script updates under load. Instead of a hard block, consider using an asynchronous status check via WebSocket events if your client supports it, or at least add exponential backoff to your JMeter test plan to mimic real-world agent behavior without overwhelming the endpoint. The documentation suggests keeping data actions lightweight; querying full conversation metadata repeatedly might timeout under high concurrency. Also, verify the region-specific latency thresholds in your architect flow. A simple retry mechanism with a max count of three attempts prevents the infinite loop issue mentioned earlier while still enforcing compliance. Ensure your load test includes these retries to accurately measure throughput.