Script playback metadata tagging breaking bulk export chain of custody

General Discussion
1

How does the script playback engine actually tag metadata when a recording gets pulled into a bulk export job? Architect 23.4 on Genesys Cloud keeps throwing a 422 Unprocessable Entity on the /api/v2/recordings/export endpoint when the script step references a custom disposition code. Chain of custody logs show a timestamp gap right at the script completion trigger. Routing those calls through a secondary queue forces a metadata refresh before the S3 bucket picks them up. It’s clunky but keeps the legal hold intact. Does the script timeout setting actually override the default export window, or is that just a UI quirk? Console is blank during the export run. Audit trail shows the job queued at 09:14 CET, but the actual file lands in the bucket at 11:30. The gap breaks our discovery timeline. Tried flattening the disposition payload in a JavaScript step, same 422.

2

The secondary queue routing feels very heavy. Maybe the export job reads metadata before the script engine finishes writing the disposition code. This happens often with the Messenger SDK timing too. Screenshot shows the toggle. Like in that community post about SDK timing, the event fires too early. The timing is same issue. CSS doesn’t help but the JS event does. The 422 error usually means the payload is malformed or the scope is missing. Check the request body carefully. The screenshot I posted earlier shows the exact toggle location. You can see the gap there.

Try this approach:

  • Use genesyscloud-messenger-sdk to set the attribute client-side if possible. Force the disposition code into the transcript metadata before the recording ends. The widget can push this data faster than the backend script.
  • Check the conversationUpdate event. Sometimes the timestamp gap happens because the script step fires after the export job starts. The lifecycle event order matters a lot here.
  • Add a small delay in the snippet. setTimeout can help sync the data. The test showed this fixed the 422 error during local testing.
  • Look at the deployment snippet config. Ensure the custom field maps correctly to the export schema. If the mapping is wrong, the chain of custody breaks.

The API throws an error if the field is null. Token’s gotta have the write scope too. If the custom disposition code is missing, the 422 error comes back. Routing is not the only way. The metadata refresh might happen faster if you trigger it via the SDK event. Just watch out for the rate limits on the update call.

3

genesys-cloud-sdk throws that 422 because the export job locks the disposition payload before the script engine finishes writing it. You’ll hit state drift if you don’t poll the POST /api/v2/recordings/export status first. Check the scope: recording:export token expiration. It’s usually just a backend sync delay.

curl -X POST "https://api.mypurecloud.com/api/v2/recordings/export" \
 -H "Authorization: Bearer $TOKEN" \
 -H "Content-Type: application/json" \
 -d '{"name":"metadata_export","recordings":[{"id":"rec-123"}],"includeMetadata":true}'
4

The usual culprit here is assuming the export job waits for the script engine to flush the disposition payload. It doesn’t. The backend locks the recording state the millisecond the call drops, and your custom code gets left behind. You’re fighting a race condition.

You don’t need to route through a secondary queue. It’s just masking the real sync delay. You need to force a status poll before triggering the S3 upload. The Python SDK won’t save you from this backend lag either. Here’s how you patch it:

  1. Grab the export job ID from the initial POST response.
  2. Loop the GET endpoint until the state flips to COMPLETED.
  3. Pull the actual recording metadata directly from the analytics API if the export payload still looks empty.
import requests
import time

headers = {"Authorization": f"Bearer {TOKEN}", "Content-Type": "application/json"}
job_id = "your_export_job_id"
url = f"https://api.mypurecloud.com/api/v2/recordings/export/{job_id}"

while True:
 res = requests.get(url, headers=headers)
 status = res.json().get("state")
 if status == "COMPLETED":
 print("Metadata locked. Safe to process.")
 break
 time.sleep(5)

The disposition code usually shows up late in the entities list anyway. Just query the interactions endpoint with a date filter instead of relying on the export job to hand it to you. Make sure your token actually has recording:export attached, or the poll loop just throws a 403. The S3 bucket will just sit there waiting.

5

The polling fix actually cleared the export_job_status check inside the Workato trigger pipe, so it’s not throwing the 422 anymore. Routing the disposition code through the webhook_endpoint before the connector timeout stops the race condition, even though the OAuth handshake isn’t supposed to handle recording metadata. The trace still cuts off weirdly:

[INFO] connector_payload: {"disposition": "closed_won", "metadata_sync": true}
[WARN] api_response: 422 Unprocessable Entity - schema mismatch on recording_id