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Fudge for Shopify

by ai.fudge
OverviewDiscussionsAdmin

List offers

list_offers
Read-onlyIdempotent

List the store’s current offers: Fudge offers, active Shopify discounts, native bundles, shipping rates by zone and free-shipping thresholds. Use for an offers or average-order-value review.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_offers"
  }
}

Input Schema

NameRequiredDescriptionDefault
storeNoThe connected store to use. Omit when only one is connected.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is fully covered by structured data. The description adds useful context beyond that: the result aggregates multiple heterogeneous sources (Fudge offers, Shopify discounts, bundles, shipping rules) and is scoped to 'current'/'active' items only, implying expired discounts are excluded. It does not say how results are ordered or shaped, so the addition is modest rather than rich.

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?

Two compact sentences with zero filler: the resource and its contents are front-loaded, and the usage hint trails it. Nothing could be removed without losing information.

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?

For a read-only list tool with one optional parameter, full schema coverage, and no output schema to explain, the description does the heavy lifting of enumerating the returned offer types across sources. Only minor gaps remain, such as ordering or how the mixed offer types are grouped in the response.

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?

There is one optional parameter whose schema description already explains the omit-when-single-store behavior at 100% coverage. The description adds nothing about 'store' beyond the schema, so the baseline 3 applies.

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?

Names a specific verb ('List') and resource ('the store's current offers'), then enumerates the concrete contents: Fudge offers, active Shopify discounts, native bundles, shipping rates by zone, and free-shipping thresholds. An agent knows exactly what data comes back, and no sibling in the catalog overlaps with this resource.

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?

Offers a single usage trigger ('Use for an offers or average-order-value review'), which is enough to imply when the tool fits. It gives no when-not conditions and names no alternative tool for related questions, so routing guidance is partial.

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

All Fudge for Shopify toolsInspect
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