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dscovr

surveymonkey-mcp

by dscovr

surveymonkey_get_contact_list

Retrieve the details of a specific SurveyMonkey contact list by supplying its list ID, including its contacts and metadata.

Instructions

Returns the details of a specific contact list.

Args: list_id: Contact list ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the burden of explaining behavior. 'Returns the details' indicates a read-only retrieval and gives a basic sense of the outcome, but it does not disclose potential errors, required permissions, or whether any side effects could occur. This is adequate but thin for a tool with no annotation safety hints.

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 extremely concise and front-loaded with the core purpose. The Args block adds necessary parameter clarification without any fluff, and every sentence earns its place.

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 simple single-parameter retrieval tool, the description is nearly complete: it states what the tool returns and identifies the required input. The presence of an output schema means return-value details do not need to be in the description, though some usage guidance relative to sibling list tools would improve completeness.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate for the parameter documentation. It does provide a meaningful gloss for list_id ('Contact list ID'), which clarifies that the parameter refers to a contact list identifier rather than another entity type. For a single simple parameter, this is sufficient semantic support.

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

Purpose4/5

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

The description clearly states the action ('Returns') and the resource ('a specific contact list'), making it easy to understand what the tool does. It does not explicitly differentiate itself from siblings like surveymonkey_list_contact_lists, but the phrase 'specific contact list' implies a singular retrieval as opposed to listing.

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 provided about when to use this tool versus alternatives such as surveymonkey_list_contact_lists or surveymonkey_get_contact. There are no exclusions, prerequisites, or context cues beyond the parameter requirement, so the agent must infer usage from the tool name and description.

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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