tenant_team_set_inference_role

WHAT IT DOES

What tenant_team_set_inference_role does on Tuning Engines - LLM Fine-Tuning

AI agents use tenant_team_set_inference_role to create or update resources in Tuning Engines - LLM Fine-Tuning — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Tuning Engines - LLM Fine-Tuning environment.

WHY IT NEEDS A POLICY

Why tenant_team_set_inference_role needs a policy

An AI agent can call tenant_team_set_inference_role faster than any human can review — one bad instruction and it creates or modifies resources in Tuning Engines - LLM Fine-Tuning by the hundred, each call as confident as the last.

Risk signalsAdmin/system-level operation

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

tenant_team_set_inference_role Rate-limited

tenant_team_set_inference_role stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "tenant_team_set_inference_role": {
      "limits": [
        {
          "counter": "tenant_team_set_inference_role_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Tuning Engines - LLM Fine-Tuning, so you can run agents against it safely.

FAQ

Questions about tenant_team_set_inference_role

What does the tenant_team_set_inference_role tool do? +

Assign or clear an inference role for a tenant member. Requires tenant owner/admin API token. It is categorised as a Write tool in the Tuning Engines - LLM Fine-Tuning MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on tenant_team_set_inference_role? +

Register the Tuning Engines - LLM Fine-Tuning MCP server in PolicyLayer and add a rule for tenant_team_set_inference_role: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Tuning Engines - LLM Fine-Tuning. Nothing to install.

What risk level is tenant_team_set_inference_role? +

tenant_team_set_inference_role is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit tenant_team_set_inference_role? +

Yes. Add a rate_limit block to the tenant_team_set_inference_role rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block tenant_team_set_inference_role completely? +

Set action: deny in the PolicyLayer policy for tenant_team_set_inference_role. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides tenant_team_set_inference_role? +

tenant_team_set_inference_role is provided by the Tuning Engines - LLM Fine-Tuning MCP server (tuningengines-cli). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.