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Glama

get_voice_consent_script

Retrieve the spoken consent script required for voice cloning in any supported language. Use it to obtain the exact wording for user consent.

Instructions

Get the spoken consent script required for voice cloning.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
language_codeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only says 'Get' (implying a read-only operation) but does not explicitly state side effects, authorization needs, rate limits, or what the script looks like. For a tool with zero annotation coverage, this is a significant gap in transparency.

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

Conciseness4/5

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

The description is a single, front-loaded sentence with no filler words. It is concise and easily parsed, but it is also so brief that it skips important details. The conciseness is good, but the structure could have included more useful information without losing clarity.

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?

This is a simple tool with one optional parameter and an output schema (not shown), so the description need not explain return values. However, it leaves gaps: it does not explain how the language_code parameter affects the script, nor does it provide any context on the content of the consent script. It is minimally adequate but incomplete for full agent understanding.

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?

The schema has one parameter (language_code) with a default value but no description, and schema description coverage is 0%. The description does not mention the parameter at all, so it adds no meaning beyond the bare name. With no coverage and no description, the agent receives no guidance on how to use the parameter, making this a serious deficiency.

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

Purpose5/5

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

The description states a specific verb ('Get'), a specific resource ('spoken consent script'), and its purpose ('required for voice cloning'). This clearly distinguishes it from sibling tools like list_voices or synthesize_audio, which perform different actions. The purpose is unambiguous and actionable.

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

Usage Guidelines3/5

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

The phrase 'required for voice cloning' implies when this tool should be used, but it does not explicitly state any alternative tools or situations where it should not be used. There is no mention of prerequisites, ordering, or context relative to other voice-related tools. The usage is implied but not fully articulated.

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