run_conversation_evaluations

Run Conversation Evaluation.

SERVERElevenlabs SOURCE@aiwerk/mcp-server-elevenlabs

High RISK CLASS

Category Execute

Parameters 32 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/aiwerk-mcp-server-elevenlabs/run-conversation-evaluations.md

WHAT IT DOES

What run_conversation_evaluations does on Elevenlabs

AI agents invoke run_conversation_evaluations to trigger actions in Elevenlabs. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.

Parameter	Type	Required	Description
`scope`	string	—
`evaluation_id`	string	Yes	ID of the single evaluation criterion to rerun.
`conversation_id`	string	Yes	ID of the conversation

Parameters from the server's own tool schema.

RISK

Why run_conversation_evaluations is rated High

run_conversation_evaluations triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs run_conversation_evaluations safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Elevenlabs, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For run_conversation_evaluations, this is the rule to start with:

run_conversation_evaluations Rate-limited

run_conversation_evaluations stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "run_conversation_evaluations": {
      "limits": [
        {
          "counter": "run_conversation_evaluations_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Elevenlabs, apply this rule, and every run_conversation_evaluations call is checked against it from then on.

FAQ

Questions about run_conversation_evaluations

What does the run_conversation_evaluations tool do? +

Run Conversation Evaluation. It is categorised as a Execute tool in the Elevenlabs MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

What parameters does run_conversation_evaluations accept? +

run_conversation_evaluations accepts 3 parameters: scope, evaluation_id, conversation_id. Required: evaluation_id, conversation_id. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on run_conversation_evaluations? +

Register the Elevenlabs MCP server in PolicyLayer and add a rule for run_conversation_evaluations: 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 Elevenlabs. Nothing to install.

What risk level is run_conversation_evaluations? +

run_conversation_evaluations is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit run_conversation_evaluations? +

Yes. Add a rate_limit block to the run_conversation_evaluations 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 run_conversation_evaluations completely? +

Set action: deny in the PolicyLayer policy for run_conversation_evaluations. 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 run_conversation_evaluations? +

run_conversation_evaluations is provided by the Elevenlabs MCP server (@aiwerk/mcp-server-elevenlabs). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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