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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

search_knowledge_base_content_route

Read-onlyIdempotent

Search knowledge base content by query. Filter by document types (file, URL, text, folder) and paginate with cursor.

Instructions

Search Knowledge Base Content

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe search query text
typesNoIf present, the endpoint will return only documents of the given types.
cursorNoUsed for fetching next page. Cursor is returned in the response.
page_sizeNoHow many documents to return at maximum. Can not exceed 100, defaults to 30.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.5/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered by structured data. The description adds nothing beyond that — no mention of pagination via cursor, the 100-item page cap, or what corpus is searched.

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

Conciseness3/5

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

The single short line has no wasted words and is front-loaded, but it is under-specified rather than genuinely concise — it conveys almost no usable information for a four-parameter search tool.

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

Completeness2/5

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

With no output schema and no description of return shape, ranking, or result scope, the definition leaves key behavior unexplained. The schema covers inputs, but the description does nothing to compensate for the absent output contract on a search endpoint.

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

Parameters3/5

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

Schema description coverage is 100%, with query, types, cursor and page_size all documented in the schema, so the baseline is 3. The description contributes no additional parameter meaning beyond what the schema already provides.

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

Purpose3/5

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

The description states a verb (Search) and a resource (Knowledge Base Content), so the basic operation is inferable, but it is essentially a restatement of the tool name/title with no differentiation from close siblings such as get_knowledge_base_content or query_agent_knowledge_base_rag_route. An agent cannot tell from this text what distinguishes this search endpoint from those alternatives.

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?

There is no when-to-use guidance at all — no indication of when this search should be preferred over get_knowledge_base_content, get_knowledge_base_list_route, or the RAG query route. The agent must infer selection purely from the name.

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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