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veterinar

retailcrm-mcp

by veterinar

list_customers

Read-only

Search and list customers by name, email, phone, or creation date. Returns customer summaries with order counts and total spent, with optional full details.

Instructions

List/search customers by name, email, phone, created-date. Returns (summary): pagination + array of {id, name, email, phone, ordersCount, totalSpent}. detail:'full' adds address/externalId/all phones.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rawNoIf true, return the untouched RetailCRM payload (for debugging; verbose).
pageNoPage number
limitNoResults per page (max 100)
detailNoOutput verbosity: 'summary' (compact, default — saves tokens) or 'full' (all shaped fields incl. line items, delivery, payments).summary
filter_nameNoFilter by customer name (partial match)
filter_emailNoFilter by email address
filter_phoneNoFilter by phone number
filter_date_toNoFilter customers created on/before (YYYY-MM-DD)
filter_date_fromNoFilter customers created on/after (YYYY-MM-DD)
Install Server

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds valuable behavioral context about the return format (pagination + array of specific fields) and the effect of detail:'full' (adds address/externalId/all phones). It does not contradict annotations and goes beyond the bare safety hint.

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 two sentences: the first states purpose and filterable fields, the second specifies return structure and detail behavior. Every word earns its place with no fluff or repetition of schema content.

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?

Given the rich schema and readOnly annotation, the description sufficiently covers return values and the key detail parameter. It does not mention filter combination logic (AND/OR) or error behavior, but these are minor gaps for a listing tool. Overall, it is complete enough for an agent to invoke correctly.

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 coverage is 100% with each parameter described, so baseline is 3. The description adds meaning by explaining the summary output fields (ordersCount, totalSpent) and clarifying that detail:'full' expands the response with additional fields, which is not explicit in the schema.

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 ('List/search') with a clear resource ('customers') and lists searchable fields (name, email, phone, created-date). It distinguishes from siblings like get_customer (single customer) and create_customer by clearly indicating a multi-result listing/search capability.

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 implies this tool is for listing/searching customers, but it does not explicitly state when to use it over alternatives (e.g., get_customer for a single record, create_customer for creation). No exclusions or alternative tool names are mentioned.

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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