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elevenlabs_requests_list

List Api Requests. Returns a list of API requests. Supports filtering by time range, column filters, and search terms. At least one of start_time or end_time must be provided. An optional sort parameter controls timestamp ordering. Results are ordered by timestamp. Descending if end_time is used, ascending if start_time is used. The response is a tabular structure with columns, column_types, column_units, and rows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNo
limitNo
searchNo
accountNo
filtersNo
end_timeNo
start_timeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

With no annotation hints (readOnlyHint false), the description carries the burden. It discloses the response format (tabular with columns, column_types, column_units, rows) and the ordering behavior. However, it omits details about pagination, rate limits, or potential side effects, making it only partially transparent.

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 concise and front-loaded with the core purpose, followed by essential usage details and response format. Every sentence adds value with no redundant or verbose content.

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?

The description covers the main functionality, filtering, ordering, and response structure, which is reasonable for a list tool. However, it does not explain 'limit', 'account', or the structure of 'filters' in detail. Given no output schema and 7 parameters, it is incomplete but not severely lacking.

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 has 7 parameters but description only explicitly explains start_time, end_time, and sort. It mentions 'column filters' and 'search terms' but does not name the parameters 'filters' or 'search' clearly. The 'limit' and 'account' parameters are completely absent. Given low schema coverage (0%), the description must compensate but only does so partially.

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?

Clear and specific: 'List Api Requests. Returns a list of API requests.' The verb 'list' and resource 'API requests' are explicit, and the description distinguishes it from other list tools (e.g., list_accounts) by focusing on API request data.

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?

Provides a critical usage condition ('At least one of start_time or end_time must be provided') and describes the sorting behavior, but does not mention alternatives or when not to use this tool. No explicit comparison to sibling tools, but context is adequate.

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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