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Survey Solutions MCP Server

Survey Solutions MCP Server

by lbruce-wq
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript

list_assignments

List Survey Solutions assignments to view responsible users, identifying data, quantities, and rules for creating interviews.

Instructions

List Survey Solutions assignments. Assignments define responsible users, identifying data, quantities, and rules used to create interviews.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_assignments"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoOptional page size for endpoints that support it.
queryNoAdvanced/raw endpoint query values. Top-level offset/limit are merged into this object.
offsetNoOptional zero-based page offset for endpoints that support it.
profileNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.7

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries full responsibility for disclosing behavior. It does not mention pagination behavior, default ordering, whether archived assignments are included, profile/workspace scoping, rate limits, or what the response contains. Saying 'List... assignments' is minimal and does not go beyond the tool name.

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

Conciseness4/5

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

The description is short and front-loaded with the primary purpose. The second sentence is not strictly operational but provides compact domain context. No redundant or verbose phrasing is present.

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?

For a list operation with four parameters, a nested query object, no annotations, and no output schema, the description is too thin. It omits essential usage context such as how to paginate, what fields can be filtered via query, how profile affects results, and what the returned assignment objects look like.

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?

The schema already documents limit, offset, and query, but the description adds no operational meaning to these parameters. The profile parameter has no schema description and is entirely unexplained in the tool description. The reference to 'quantities and rules' is conceptual and does not help an agent understand query filtering or parameter semantics.

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 opens with a specific verb-plus-resource statement, 'List Survey Solutions assignments,' which clearly identifies the operation and resource. The follow-up sentence provides useful domain context about what assignments are. However, it does not explicitly differentiate this list operation from related siblings like get_assignment or get_assignment_history.

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 guidance about when to use list_assignments versus alternatives such as get_assignment, create_assignment, or get_assignment_history. No conditions, exclusions, or recommended scenarios are provided, so the agent must infer usage from the name alone.

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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