I am building an automated skill management tool for one of my agency clients. The tool needs to bulk-update agent routing skills based on training completion data from their LMS.
The API call to update user routing skills appears to succeed - I get a 200 response with the updated skill list in the response body. But when I immediately query the user’s skills afterward, the changes are not there. The user still has their original skill set.
Here is my flow:
import PureCloudPlatformClientV2 as purecloud
api = purecloud.RoutingApi()
# Step 1: Get current skills
current = api.get_user_routingskills(user_id)
print(f"Before: {[s.name for s in current.entities]}")
# Step 2: Add new skill
body = purecloud.UserRoutingSkillPost()
body.id = new_skill_id
body.proficiency = 3.0
result = api.post_user_routingskills(user_id, body)
print(f"API Response: {result.id} - {result.name}") # Shows new skill!
# Step 3: Verify
updated = api.get_user_routingskills(user_id)
print(f"After: {[s.name for s in updated.entities]}")
# Still shows original skills only!
The response in Step 2 includes the new skill. But Step 3 shows no change. If I wait 5 minutes and query again, sometimes the skill appears and sometimes it does not. This is for multiple users, not just one.
We are running this against the ap-northeast-1 (Tokyo) region. Is there eventual consistency issue with the routing skills API?
Yeah this is a known eventual consistency issue with the routing skills subsystem. I actually filed a bug on the Genesys Cloud Python SDK GitHub repo about this (issue #847).
The routing skills API writes to a distributed cache that feeds the ACD routing engine. The GET endpoint reads from a different replica of that cache. After a POST/PUT, the write replica updates immediately (which is why the response looks correct), but the read replica takes 1-30 seconds to sync.
The reliable workaround is to add a polling loop with exponential backoff:
import time
def wait_for_skill(api, user_id, skill_id, max_wait=60):
wait = 2
elapsed = 0
while elapsed < max_wait:
time.sleep(wait)
elapsed += wait
skills = api.get_user_routingskills(user_id)
if any(s.id == skill_id for s in skills.entities):
return True
wait = min(wait * 2, 15)
return False
For bulk operations across hundreds of users, do NOT query after each individual skill update. Batch all your POST calls first, then do a single verification pass after a 30-second cooldown. This dramatically reduces your API call count and stays within rate limits.
Eventual consistency is the root cause. One more detail: if you are migrating from CXone, be aware that CXone’s skill assignment is synchronous. The same code pattern that works instantly on CXone will exhibit this lag on GC.
Factor the verification delay into your migration timeline estimates.
We encountered this same issue when building our chatbot skill routing integration. The polling approach works for batch operations, but if your use case requires the skill to be active on the agent before the next inbound interaction routes, there is a more deterministic approach.
Instead of polling the GET endpoint, subscribe to the WebSocket notification topic v2.users.{userId}.routingStatus. When the skill update propagates to the routing engine, the notification channel emits a routing status event. This is a push notification rather than a poll, so you know the exact moment the skill becomes active for routing.
This is critical for real-time scenarios where a customer is waiting in queue and you need to dynamically assign a skill to an available agent to handle a specialized request.