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MCPGeneration-for-ElevenLabs

MCPGeneration-for-ElevenLabs

list_generation_history

Retrieve ElevenLabs speech generation history with filters for voice, model, date, and search to track past audio outputs.

Instructions

List ElevenLabs speech generation history with documented filters.

Input Schema

NameRequiredDescriptionDefault
searchNo
sourceNo
model_idNo
voice_idNo
page_sizeNo
sort_directionNo
date_after_unixNo
date_before_unixNo
start_after_history_item_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.1/5.0
Behavior2/5

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

With no annotations at all, the description carries the full behavioral burden and adds essentially nothing: "List" weakly implies a read-only, non-destructive operation, but there is no disclosure of pagination mechanics, default page size, sort defaults, result caps, auth or scope requirements, or timestamp units. The cursor-style parameter start_after_history_item_id hints at pagination, yet the description never confirms or explains it.

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

Conciseness3/5

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

The single sentence is front-loaded and wastes no tokens on preamble, which is a genuine strength. But the closing phrase "with documented filters" is pure filler that promises documentation the definition does not deliver, and the extreme brevity here reads as under-specification rather than economy.

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?

For a nine-parameter, filter-heavy list tool with zero schema description coverage, no annotations, and no output schema, the definition is far too thin to support correct invocation. An agent cannot determine filter value formats, pagination behavior, default and maximum result sizes, or what a history item contains without trial and error.

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 0% across nine parameters, and the description claims "documented filters" while documenting none of them. Ambiguous fields like source (what values?), date_after_unix vs date_before_unix (epoch seconds? milliseconds? timezone?), and start_after_history_item_id (cursor semantics) are left entirely unexplained in both the schema and the description.

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

Purpose3/5

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

The description names a specific verb and resource ("List ... speech generation history") and pins the provider as ElevenLabs, which separates it from singular siblings like get_generation_history_item. However, the trailing clause "with documented filters" is a content-free qualifier, and nothing distinguishes this from adjacent list tools such as list_generated_assets or list_image_generations beyond the domain noun.

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 when-to-use guidance, no exclusions, and no mention of the alternatives an agent should consider (get_generation_history_item for a single item, download_history_audio for retrieval, get_api_request_history for request-level logs). The agent must infer selection purely from the tool name.

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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