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@aiwerk/mcp-server-elevenlabs

@aiwerk/mcp-server-elevenlabs

by AIWerk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

get_agent_knowledge_base_size

Read-onlyIdempotent

Retrieve the size of an ElevenLabs agent's knowledge base by agent ID to monitor content volume and plan updates.

Instructions

Returns The Size Of The Agent'S Knowledge Base

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "agent_id": "<agent_id>"
    },
    "name": "get_agent_knowledge_base_size"
  }
}

Input Schema

NameRequiredDescriptionDefault
agent_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint. The description adds no additional behavioral context such as what 'size' measures, auth requirements, or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single concise sentence with no wasted words. It front-loads the action and is appropriately sized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read endpoint with rich annotations, the description is mostly adequate. It leaves the meaning of 'size' and the required agent_id undocumented, and with no output schema some ambiguity remains acceptable but noticeable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The one required agent_id parameter has 0% schema description coverage. The description only implies an agent via the possessive 'Agent's' and gives no format, source, or required nature, so it fails to compensate for the schema gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a clear specific verb and resource: returns the size of an agent's knowledge base. It does not explicitly differentiate from siblings such as get_agent_knowledge_base_summaries_route or get_knowledge_base_content, so scope must be inferred.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides no when-to-use guidance or alternatives. It does not say when to prefer this over summaries or content endpoints.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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