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UVU-Store

shopify-graphql-mcp

by UVU-Store

cancel_customer_data_erasure

Cancel a pending customer data erasure request under GDPR before processing begins. Provide the customer ID to halt the erasure.

Instructions

Cancel a pending customer data erasure request (GDPR). Can only cancel requests that haven't started processing yet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customerIdYesCustomer ID for whom to cancel the pending data erasure
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly discloses a critical limitation (only pending requests can be cancelled) and introduces the GDPR context, which implies a sensitive data-handling operation. This is adequate for a simple cancellation tool, though it could mention side effects or error behavior.

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, front-loaded with the action verb, and contains zero filler. Every word contributes meaning, efficiently conveying the purpose and the key precondition.

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 simplicity of the tool (one parameter, no output schema, no nested objects), the description adequately covers the essential aspects: what it does and when it can be used. The GDPR context adds necessary framing. It does not explain return values, but for a cancellation action this is usually implied and not critical.

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?

The input schema already provides 100% coverage with a clear description for the single parameter 'customerId'. The tool description adds no extra meaning about the parameter beyond what the schema states, so the baseline score of 3 is appropriate.

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 uses a specific verb 'Cancel' and identifies the resource as 'pending customer data erasure request (GDPR)', distinguishing it from sibling tools like 'request_customer_data_erasure' (which creates such requests) and 'get_customer_data_erasure_requests' (which lists them). It unambiguously states the tool's function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear usage constraint: 'Can only cancel requests that haven't started processing yet.' This tells the agent when to use the tool (pending requests only) and implies when not to (already processing). It does not explicitly name alternative tools, but the condition is practical and contextually sufficient.

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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