Delete Dubbing Language Target. Delete a language target.
Bulk support: accepts project_ids, language_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | ||
| project_id | Yes | ||
| language_id | Yes | ||
| project_ids | No | ||
| language_ids | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description says 'Delete,' which implies a destructive action, but the annotations set destructiveHint to false, creating a direct contradiction. Additionally, the description does not disclose consequences like irreversibility, permission requirements, or side effects. Since the description contradicts the annotation, the score is 1.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no extraneous information. It front-loads the purpose and adds a concise note about bulk support. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive operation with no annotations (except false hints) and no output schema, the description is too sparse. It omits crucial context such as irretrievability, permission prerequisites, or how batch mode differs from single mode. The lack of behavioral transparency and usage guidance makes it incomplete for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning to some parameters by mentioning bulk support with project_ids and language_ids for batched execution. This clarifies the purpose of the array parameters. However, it does not explain the account parameter or the relationship between project_id/language_id and their list counterparts. Given 0% schema coverage, it partially compensates but leaves gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Delete Dubbing Language Target' and 'Delete a language target,' which is specific about the resource and operation. It distinguishes from siblings like dubbing_language_create or list, though it doesn't contrast with overlapping delete tools like dubbing_project_delete. The purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 such as delete_dubbing or dubbing_project_delete. The mention of bulk support is a parameter behavior hint, not a usage guideline. No prerequisites or context for when to choose batch vs single deletion are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
There are many tools with overlapping purposes, such as multiple voice retrieval tools (get_voice_by_id, get_voices, get_user_voices_v2, get_library_voices) and several dubbing transcript segment editors with only subtle naming differences. The inclusion of platform-level tools (authenticate, connect, marketplace) alongside ElevenLabs API tools further blurs boundaries.
Naming is highly inconsistent. Most tools have the 'elevenlabs_' prefix, but some do not (authenticate, connect, marketplace, report_bug, show_version, toolkit_info). Several tools have truncated/random suffix names (e.g., elevenlabs_dubbing_target_transcript_segmen_b565e6, elevenlabs_get_pronunciation_dictionary_ver_45baf2), and one tool is in Portuguese (elevenlabs_list_accounts). This mixture of conventions and languages makes the pattern unpredictable.
With 155 tools, the server is extremely bloated. It mixes a comprehensive ElevenLabs API surface with unrelated MCP platform tools (marketplace, authenticate, report_bug, etc.) that belong in a separate toolkit. This is a severe mismatch between the apparent purpose (ElevenLabs audio services) and the sheer number of tools.
The ElevenLabs-specific tools cover a wide range of operations (text-to-speech, voice management, dubbing, pronunciation dictionaries, Studio projects, workspace administration, order management), making it fairly complete for those domains. However, the inclusion of unrelated platform tools and the lack of a clear focus mean that an agent would have difficulty navigating this large surface, and some operations like music finetuning or speech engines appear only partially covered.