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JamBelg

MCP GraphQL Sales Server

by JamBelg

get_total_spent_by_customer

Compute total spending for a specified customer by name. Returns the aggregate amount spent, helping assess customer value and purchase history.

Instructions

Get the total amount spent by a customer.

Args:
    customer_name: The customer name to calculate total spending for

Returns:
    Dict containing the total spent or error information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customer_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses that the return is a dict containing total spent or error information, which gives some transparency. However, it does not explicitly state that the operation is read-only, how errors are represented, or whether customer_name requires exact match.

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 compact and well-structured with Args/Returns sections. Every sentence earns its place, and there is no redundant fluff beyond the slightly repetitive parameter explanation.

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

Completeness3/5

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

Given the tool's low complexity (one parameter) and the presence of an output schema, the description is adequate for basic invocation. However, it lacks usage context relative to sibling tools, making it less complete for an agent deciding between options.

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 has no property descriptions (coverage 0%), so the description must compensate. Yet it only repeats the parameter name ('customer_name') with a near-identical phrase, adding no extra meaning about format, case sensitivity, or examples. Minimal value beyond 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 clearly states the action ('Get the total amount spent') and the resource (a customer). It distinguishes itself from sibling tools like 'get_orders_by_customer_name' or 'get_order_summary' by focusing specifically on total spend.

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 on when to use this tool versus alternatives. There is no mention of required input format, exact matching, or scenarios such as 'use this for aggregated spending' versus other order-level tools.

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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