400 error updating predictive routing skill weights via Studio REST proxy

Genesys Cloud Routing
1

Trying to update predictive routing skill weights from a Studio script using a REST proxy action. The documentation for the PUT /api/v2/routing/agents/{agentId}/skills endpoint states: “The request body must contain an array of skill objects where each object includes a valid skill_id and a numeric weight value between 0 and 1.0.”

We’re sending exactly that. The payload looks clean. Studio logs show the request goes out, but the response comes back with a 400 error.

{
 "code": "invalid_skill_configuration",
 "message": "Skill weight array contains non-numeric value or missing required field.",
 "status": 400
}

Using CXone Studio version 24.2. The script assigns the weight via a variable, casts it to float. Debug trace shows 0.85 in the payload. Yet the API rejects it. Checked the skill ID against the catalog endpoint, it’s a direct copy-paste match. The docs explicitly mention that “weight values must be provided as floating-point numbers without scientific notation” so the value is passed as 0.75 directly. Console output confirms the JSON structure is valid. Why is the endpoint throwing a validation error when the payload matches the schema definition word for word?

2

PureCloudPlatformClientV2 requires the routing_skills wrapper key for the PUT /api/v2/routing/agents/{agentId}/skills endpoint. You don’t send a raw array.

{ "routing_skills": [ { "id": "a1b2c3", "weight": 0.75 } ] }

Drops 400 when that parent object is missing. Just check the proxy response headers.

3

That wrapper key is mandatory. Studio proxies strip the outer object if you don’t wrap the payload in routing_skills first, so try this exact shape:
{ "routing_skills": [{ "id": "a1b2c3", "weight": 0.75 }] }
Studio defaults that header to form-urlencoded half the time.

4
  • Wrapped the payload in routing_skills, but the 400 still fires. Try wrapping it again with strict JSON formatting.
  • Forced the header to application/json. Studio’s defaulting to form-urlencoded. Lock the header manually.
  • Checked the schema validation logs. It’s rejecting untyped objects. Verify the weight field is a float, not a string.
  • What exact Content-Type header is the proxy actually pushing out?
5

The routing_skills wrapper and application/json header are definitely the baseline fix. Studio’s proxy action strips outer objects if the JSON isn’t strictly formatted. The API parser also rejects string-typed weights instantly. You’ll hit a hard 400 if the payload contains "0.75" instead of a raw 0.75. The system doesn’t parse strings either.

A quick A/B test on weight precision last quarter showed the predictive routing model choking on values past three decimal places. The algorithm expects standard float formatting. Something like 0.750 gets truncated internally, and the ML scoring engine drops the agent from the candidate pool until the next calibration cycle.

Hardcode the weight as a raw number in the Studio script action. Force the Content-Type to application/json in the proxy headers. Check the agent’s current skill set in the admin console before pushing the update. The endpoint performs a full replace, not a merge. Accidentally wiping an existing skill makes the predictive model ghost that agent for the whole queue.

Watch out for the calibration lag too. The AI outcomes engine takes about 15 minutes to retrain on new weight distributions. Pushing updates during peak hours usually tanks first-call resolution metrics until the model recalibrates.