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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

get_conversation_users_route

Read-onlyIdempotent

Retrieve and filter conversation users by agent, branch, user ID, or date range, with sorting by last contact, conversation count, or average sentiment.

Instructions

Get Conversation Users

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoUsed for fetching next page. Cursor is returned in the response.
searchNoSearch/filter by user ID (exact match).
sort_byNoThe field to sort the results by. Defaults to last_contact_unix_secs.
agent_idNoAgent id (agent_…) or speech engine external id (seng_), resolved to the same underlying resource.
branch_idNoFilter conversations by branch ID.
page_sizeNoHow many users to return at maximum. Defaults to 30.
sort_directionNoThe direction to sort the results
call_start_after_unixNoUnix timestamp (in seconds) to filter conversations after to this start date.
call_start_before_unixNoUnix timestamp (in seconds) to filter conversations up to this start date.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.2/5.0
Behavior2/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, and the description adds no behavioral context beyond them. It does not mention pagination, default limits, filtering behavior, or what 'conversation users' means.

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

Conciseness2/5

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

The description is only four words and is under-specified rather than effectively concise. For a tool with nine optional filtering and pagination parameters, it does not front-load enough information to guide invocation.

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?

Although annotations cover safety and the schema covers parameters, the description omits critical context for a 9-parameter conversation-user listing tool: scope, intended use cases, and differentiation from siblings. No output schema exists to compensate for the missing return-value context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all nine parameters are documented in the schema. The description adds no parameter meaning, but the baseline is 3 when the schema carries the full parameter semantics.

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

Purpose2/5

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

The description 'Get Conversation Users' is a tautological restatement of the tool name/title, adding no scope, actor, or distinction from siblings such as get_assignable_users_route or get_workspace_members.

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?

No guidance is given about when to use this tool versus alternatives. With many user-listing and conversation-related siblings, the absence of routing context leaves selection ambiguous.

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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