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@aiwerk/mcp-server-elevenlabs

@aiwerk/mcp-server-elevenlabs

by AIWerk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

remove_rules

Delete specified pronunciation rules from an ElevenLabs pronunciation dictionary by providing its ID and the rule strings to remove.

Instructions

Remove Rules From The Pronunciation Dictionary

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": {
      "pronunciation_dictionary_id": "<pronunciation_dictionary_id>",
      "rule_strings": "<rule_strings>"
    },
    "name": "remove_rules"
  }
}

Input Schema

NameRequiredDescriptionDefault
rule_stringsYesList of strings to remove from the pronunciation dictionary.
pronunciation_dictionary_idYesThe id of the pronunciation dictionary

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior1/5

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

The description adds no behavioral context beyond the name. It also contradicts the annotations: the tool is called remove_rules and described as removing rules, while destructiveHint is false, indicating the tool performs only additive updates. This is an annotation contradiction.

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?

The description is a single, front-loaded phrase with no wasted words. It is appropriately sized for a simple two-parameter removal tool, even if additional detail would be useful elsewhere.

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?

For a mutation tool with no output schema, the description does not explain effects, prerequisites, error behavior, or alternatives. The schema covers parameters, but the definition is incomplete regarding operational context.

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%, so both parameters are already documented in the schema. The description adds no additional semantic detail about rule_strings or pronunciation_dictionary_id, so the baseline of 3 is appropriate.

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?

The description states a clear verb and resource: remove rules from a pronunciation dictionary. It is specific enough to distinguish this from unrelated siblings, but it does not explicitly differentiate itself from closely related tools such as add_rules or set_rules.

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 alternatives like add_rules, set_rules, or patch_pronunciation_dictionary. The implied usage is obvious from the name, but no conditions, prerequisites, or exclusions are provided.

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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