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AbbottDevelopments

Shopmonkey MCP Server

search_customers

Search customer records in Shopmonkey by query string, with pagination support for large result sets.

Instructions

Search customers in Shopmonkey by query string. Supports full-body search with pagination.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skipNoNumber of records to skip for pagination (default: 0)
limitNoMaximum number of results to return (default: 25)
queryNoSearch query to filter customers by name or other fields
locationIdNoFilter by location ID. Defaults to SHOPMONKEY_LOCATION_ID env var if set.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.1

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states that it supports pagination, which is useful, but it does not mention that this is a read-only operation, what the return format looks like, or any limitations (e.g., rate limits). For a search tool, the read-only nature is implied but not explicit. The description adds some value but lacks detail.

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 sentences with no filler. The core purpose is front-loaded, and the key feature (full-body search with pagination) is stated efficiently. Every word 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 search tool with no output schema, the description is fairly complete: it names the resource, method, and pagination support. It does not explicitly state that it returns a list of matching customers, but that is a reasonable inference from 'search customers'. Given the low complexity and full schema coverage, the definition is adequate, though it could mention the return type for absolute clarity.

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 four parameters (skip, limit, query, locationId) are documented. The description mentions 'query string' and 'pagination', which aligns with the query and skip/limit parameters, but it does not add meaning beyond the schema. Baseline 3 is appropriate since the schema already explains the parameters.

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?

States a specific verb (search) and resource (customers) with a method (query string). It mentions 'full-body search' which implies a general search across fields, but does not explicitly differentiate from siblings like search_customers_by_email or search_customers_by_phone. The purpose is clear but sibling distinction is implicit.

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?

The description mentions full-body search and pagination, giving some context for when to use it. However, it does not explicitly state when to prefer this over the more specific search_customers_by_email or search_customers_by_phone tools. An agent would have to infer that this is the general-purpose search. No exclusions or alternative recommendations are provided.

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