@aiwerk/mcp-server-elevenlabs

update_speech_engine

Modify an existing speech engine's ASR, TTS, and VAD settings, along with turn detection and privacy options, by providing its ID and updated parameters.

Instructions

Update Speech Engine

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": {
      "speech_engine_id": "<speech_engine_id>"
    },
    "name": "update_speech_engine"
  }
}

Input Schema

Name	Required	Description
`asr`	No
`tts`	No
`vad`	No
`name`	No
`tags`	No
`turn`	No
`privacy`	No
`language`	No
`overrides`	No
`call_limits`	No
`conversation`	No
`speech_engine`	No
`speech_engine_id`	Yes	The speech engine ID (accepts seng_ or agent_ prefix)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 13, 2026

TDQS

D1.5/5.0

Behavior1/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false, destructiveHint=false and openWorldHint=true, so the safety profile is covered structurally; the description adds zero behavioral context beyond them. It does not say what gets overwritten, whether partial updates are supported, or any auth/rate constraints.

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

Conciseness2/5

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

Three words carry no waste but also no information; this is under-specification rather than true conciseness. For a 13-parameter mutation tool, the brevity is a deficiency, not a virtue.

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

Completeness1/5

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

Given 13 parameters, 8% schema coverage, no output schema, and only baseline annotations, the definition is completely inadequate for calling the tool correctly. An agent cannot determine what fields to send, what changes, or what preconditions apply.

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

Parameters1/5

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

Schema description coverage is only 8% across 13 parameters, many of which are nested objects (asr, tts, vad, turn, privacy, call_limits, conversation, speech_engine). With such low coverage the description must compensate, and it supplies no parameter meaning whatsoever, not even for the required speech_engine_id.

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

Purpose2/5

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

"Update Speech Engine" merely restates the tool name and title with no additional specificity. It does state a verb and resource, but nothing distinguishes it from the other speech-engine siblings (create/delete/get/list_speech_engine) or clarifies what updating entails.

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 guidance on when to use this tool versus create_speech_engine, get_speech_engine, or delete_speech_engine, nor any prerequisites such as needing an existing speech_engine_id. The description provides no usage context at all.

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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