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Solutif Genesys Cloud MCP Server

search_voice_conversations

Find voice conversations in a date range, optionally filtered by phone number, to retrieve paginated conversation IDs and call durations for analysis.

Instructions

Searches for voice conversations within a specified time window, optionally filtering by phone number. Returns a paginated list of conversation IDs and call duration for use in further analysis or tool calls.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endDateYesThe end date/time in ISO-8601 format (e.g., '2024-01-07T23:59:59Z')
pageSizeNoThe maximum number of conversations to return per page. Defaults to 100 if not specified. Used with 'pageNumber' for pagination. The maximum value is 100
startDateYesThe start date/time in ISO-8601 format (e.g., '2024-01-01T00:00:00Z')
pageNumberNoThe page number of the results to retrieve, starting from 1. Defaults to 1 if not specified. Used with 'pageSize' for navigating large result sets
phoneNumberNoOptional. Filters results to only include conversations involving this phone number (e.g., '+440000000000')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations provide only a title, so the description carries the behavioral disclosure burden. It states that this is a search returning a paginated list of conversation IDs and call duration, implying read-only metadata retrieval and explicitly excluding transcript content. It does not cover ordering, error behavior, or rate limits, but these are relatively minor for a simple search tool.

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 front-load the core action and scoping criteria, then state the output. Every clause contributes useful information with no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema, the description adequately specifies the return shape (IDs and duration) and pagination, while the schema fills in parameter details. It could add ordering or empty-result behavior, but nothing essential for selecting and invoking the tool is missing.

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?

The input schema already documents all five parameters with descriptions, examples, and constraints, providing 100% coverage. The description only restates the high-level window, phone filter, and pagination concepts without adding parameter-specific detail beyond the schema, which matches the baseline score.

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?

The description uses a specific verb ('Searches') tied to a clear resource ('voice conversations') and adds scoping criteria: a time window and optional phone-number filter. It also states the returned payload (conversation IDs and call duration), which distinguishes it from transcript, sentiment, and topic sibling tools that return content or analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly frames when to use the tool: finding voice conversations within a date range, optionally filtered by phone number, to obtain metadata for further analysis. It does not, however, name sibling alternatives or state when not to use it, so it lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.