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MCPGeneration-for-ElevenLabs

MCPGeneration-for-ElevenLabs

add_dubbing_language

Add a target-language job to a dubbing project, with optional paid and unknown-cost allowances to control separate language charges.

Instructions

Add one target-language job to a dubbing project. A language target may incur separate charges.

Input Schema

NameRequiredDescriptionDefault
allow_paidNo
project_idYes
target_languageYes
allow_unknown_costNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does add one genuinely useful behavioral fact: a language target may incur separate charges. However, it is silent on the critical paid-consent gating implied by the allow_paid and allow_unknown_cost flags, on whether the job runs asynchronously, and on what happens on failure or duplicate language targets.

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?

Two short sentences with the action stated first and the cost caveat second; nothing is redundant or buried. The description is front-loaded and easy to scan.

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 four-parameter mutation tool with no annotations, no schema descriptions, and no output schema, the description is too thin. It omits the consent semantics of the boolean flags, the async nature of the resulting job, and how to check progress, leaving the agent under-informed about how to call it safely.

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?

Schema description coverage is 0%, so the description must compensate for all four parameters. It only gestures at project_id and target_language via prose ('to a dubbing project', 'target-language job'), and never explains the two boolean flags that determine whether a paid job is permitted. The 'may incur separate charges' line hints at cost but does not connect it to allow_paid or allow_unknown_cost.

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 gives a specific verb+resource: add one target-language job to a dubbing project. That is clearly distinct from siblings such as create_dubbing_project or get_dubbing_status, so an agent can place it in the dubbing workflow. It stops short of naming an explicit alternative, which keeps it from a 5.

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?

The phrase 'to a dubbing project' implies a project must already exist, but the description never states prerequisites or when to use this versus create_dubbing_project or get_dubbing_status. There are no exclusions and no guidance on calling it repeatedly for multiple languages.

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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