Skip to main content
Glama
UVU-Store

shopify-graphql-mcp

by UVU-Store

get_resource_feedbacks

Retrieve customer feedbacks for Shopify products and collections, with filtering by resource type and pagination support.

Instructions

Fetch resource feedbacks from the Shopify store

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNoCursor for pagination
firstNoNumber of feedbacks to fetch (1-250, default: 50)
resourceTypeNoFilter by resource type
Behavior2/5

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

With no annotations provided, the description must carry the behavioral disclosure burden. It only says 'Fetch resource feedbacks' which implies a read operation, but it does not explicitly state read-only behavior, pagination, filtering capabilities, or any side effects or permissions. This is minimal disclosure.

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

Conciseness3/5

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

The description is a single sentence, which is concise and front-loaded with the verb. However, the phrase 'from the Shopify store' is redundant given the context, adding minimal value and wasting a few words.

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

Completeness2/5

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

The tool is simple with three optional parameters and no output schema, but the description lacks any mention of pagination, filtering by resourceType, or default values. It does not explain what a successful response contains, which would be helpful since there is no output schema. Overall, the description is too sparse for a complete understanding.

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 full descriptions for all three parameters (after, first, resourceType) with 100% coverage. The description adds no additional parameter-specific meaning, so the baseline 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 uses the specific verb 'Fetch' with the clear resource 'resource feedbacks', making the tool's purpose immediately obvious. It distinguishes itself from the sibling create_resource_feedback by focusing on retrieval rather than creation, and the resource name is unique among siblings.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention that it is for reading existing feedbacks or contrast it with create_resource_feedback, nor does it indicate any prerequisites or context.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/UVU-Store/shopify-graphql-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server