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AIWerk

@aiwerk/mcp-server-ghl

by AIWerk

store_get_available_shipping_zones

Read-only

Retrieve available shipping zones for an order using country, order amount, weight, source, and product data to determine applicable shipping rates.

Instructions

Get available shipping rates

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
altIdNoLocation Id or Agency Id Defaults to GHL_LOCATION_ID when omitted.
sourceYesSource of the order
addressNoAddress of the customer
altTypeNoDefaults to GHL_LOCATION_ID when omitted.
countryYesCountry code of the customer
productsYesAn array of price IDs and quantity
couponCodeNoCoupon code
amountAvailableNoit will not calculate the order amount form backend if it is true
weightAvailableNoFlag to pass when the weight is already calculated and should not calculate again
totalOrderAmountYesThe amount of the price. ( min: 0.01 )
totalOrderWeightYesEstimated weight of the order calculated from the order creation side in kg(s)
Behavior2/5

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

Annotations indicate readOnlyHint=true and destructiveHint=false, so the safety profile is covered. However, the description adds no additional behavioral context such as side effects, dependencies, or error conditions. It merely restates the tool's basic function without enriching the annotation-provided information.

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

Conciseness2/5

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

The description is extremely short (four words), which is concise, but it sacrifices essential information. It does not front-load any differentiating details or use cases. Conciseness is fine, but the under-specification makes it insufficient.

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

Completeness1/5

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

With 11 parameters, nested objects, and no output schema, the description provides almost no contextual completeness. It does not explain what the tool returns, how it relates to shipping zones vs rates, or any operational nuances. This is far below the minimum viable for a complex tool.

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 parameters are documented in the schema. The tool description adds no additional semantic meaning beyond what the schema already provides. Thus, 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.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a verb ('get') and a resource ('shipping rates'), but the tool name refers to 'shipping zones,' creating ambiguity. It does not distinguish from sibling tools like store_get_shipping_rates or store_get_shipping_zones, so an agent cannot easily tell them apart.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool versus alternatives. No context, prerequisites, or exclusions are provided. The description is a single sentence with no usage direction.

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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