get_public_llm_expected_cost_calculation
Calculate Expected Llm Usage.
This record as markdown: /tools/aiwerk-mcp-server-elevenlabs/get-public-llm-expected-cost-calculation.md
What get_public_llm_expected_cost_calculation does on Elevenlabs
AI agents call get_public_llm_expected_cost_calculation to retrieve information from Elevenlabs without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
rag_enabled | boolean | Yes | Whether RAG is enabled. |
prompt_length | number | Yes | Length of the prompt in characters. |
number_of_pages | number | Yes | Pages of content in PDF documents or URLs in the agent's knowledge base. |
Parameters from the server's own tool schema.
Why get_public_llm_expected_cost_calculation is rated Low
Even though get_public_llm_expected_cost_calculation only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs get_public_llm_expected_cost_calculation 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 get_public_llm_expected_cost_calculation, this is the rule to start with:
get_public_llm_expected_cost_calculation is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Elevenlabs, apply this rule, and every get_public_llm_expected_cost_calculation call is checked against it from then on.
Questions about get_public_llm_expected_cost_calculation
Calculate Expected Llm Usage. It is categorised as a Read tool in the Elevenlabs MCP Server, which means it retrieves data without modifying state.
get_public_llm_expected_cost_calculation accepts 3 parameters: rag_enabled, prompt_length, number_of_pages. Required: rag_enabled, prompt_length, number_of_pages. The full parameter table on this page comes from the server's own tool schema.
Register the Elevenlabs MCP server in PolicyLayer and add a rule for get_public_llm_expected_cost_calculation: 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.
get_public_llm_expected_cost_calculation is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_public_llm_expected_cost_calculation 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.
Set action: deny in the PolicyLayer policy for get_public_llm_expected_cost_calculation. 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.
get_public_llm_expected_cost_calculation 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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