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lightbulb-mcp

lightbulb-mcp

by RPasquale
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

shopify_list_refunds

Read-onlyIdempotent

List recent refunds in the shop, optionally filtered by order ID, with a configurable limit.

Instructions

List recent order refunds in the shop.

Args: limit: Maximum refunds to return (1-250). order_id: Optional order ID to scope refunds to a single order. project_id: Authenticated Project UUID. project_ref: Exact project correlation reference. connector_account_ref: Project-bound connector account alias. idempotency_key: Stable business-action identity. effect: Required and must be read; Spring verifies it. approval_ref: Approved platform task UUID when resuming a write.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "effect": "<effect>"
    },
    "name": "shopify_list_refunds"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
effectYes
order_idNo
project_idNo
project_refNo
approval_refNo
idempotency_keyNo
connector_account_refNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changedv0.1.1
    • addedInput schema / properties / approval_ref
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Approval Ref"
+}
    • addedInput schema / properties / connector_account_ref
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Connector Account Ref"
+}
    • addedInput schema / properties / effect
      Added value: +{
+  "const": "read",
+  "title": "Effect",
+  "type": "string"
+}
    • addedInput schema / properties / idempotency_key
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Idempotency Key"
+}
    • addedInput schema / properties / project_id
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Project Id"
+}
    • addedInput schema / properties / project_ref
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Project Ref"
+}
    • addedInput schema / required
      Added value: +[
+  "effect"
+]
  2. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description reinforces this with 'effect: Required and must be read; Spring verifies it,' but it also includes 'approval_ref: Approved platform task UUID when resuming a write,' which is confusing in a read-only list tool and could mislead an agent.

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

Conciseness4/5

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

The description is compact and front-loads the purpose in one sentence, followed by a structured parameter list. Every line adds some information, though several parameter descriptions are terse enough to feel like repetitive boilerplate.

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 output schema exists and annotations cover safety, the parameter list is mostly adequate for invoking the tool. However, the description lacks usage context, pagination behavior, sorting semantics, and clarity on how project_id, project_ref, and connector_account_ref relate to one another.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry the semantic load, and it does for most parameters: limit is given a 1-250 range, order_id is described as scoping to a single order, and effect is explained as required and read-only. Some descriptions are generic boilerplate (e.g., project_ref and connector_account_ref), but they still add meaning beyond raw types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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

The description states a specific action and resource: 'List recent order refunds in the shop.' This is clear and uses a concrete verb, but it does not differentiate from closely related sibling tools such as shopify_list_transactions or square_list_refunds, and 'recent' is left undefined.

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?

There is no guidance on when to use this tool versus alternatives, no mention of prerequisites, and no exclusions. The description simply says what the tool does and then dives into parameters, leaving the agent to infer the appropriate context.

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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