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E-Commerce Support Agent MCP Server

E-Commerce Support Agent MCP Server

by CuriousMonkey414
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

cancel_order

Cancel a customer's order after verifying ownership and cancellable status. Use preview mode first to confirm the order details, then confirm to finalize.

Instructions

Cancel an order belonging to a specific customer.

This is a state-changing operation, gated the same way as the in-process agent: the order must exist, must belong to customer_id, and must be in a cancellable state (Pending or Processing). Call with confirmed=False first to preview the result without cancelling anything; call again with confirmed=True only after the customer has explicitly confirmed that specific order.

The calling client remains responsible for authenticating the customer before invoking this tool.

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": {
      "order_id": "<order_id>",
      "customer_id": "<customer_id>",
      "confirmed": "<confirmed>"
    },
    "name": "cancel_order"
  }
}

Input Schema

NameRequiredDescriptionDefault
order_idYes
confirmedYes
customer_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A5/5.0
Behavior5/5

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

With no annotations provided, the description fully carries the burden of disclosing behavior. It clearly states this is a state-changing operation, explains the confirmation flow prevents accidental cancellation, and explicitly notes the authentication responsibility. It also indirectly signals irreversibility by contrasting 'preview' with 'without cancelling anything.'

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 well-structured: a concise opening statement, then a logical flow covering preconditions, the two-step confirmation process, and the client's responsibility. Each sentence earns its place, and the formatting (paragraph breaks) aids readability without unnecessary verbosity.

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

Completeness5/5

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

Given the tool's complexity (destructive state change, conditional gating, confirmation flow), the description covers all critical aspects: preconditions, cancellation states, preview/confirm workflow, and security responsibility. The presence of an output schema means return values need not be described, so the description is complete for safe and correct usage.

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

Parameters5/5

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

Even though the input schema has no parameter descriptions (0% coverage), the description explains the semantics of all three parameters: order_id must exist and be cancellable, customer_id must own the order, and confirmed controls preview vs. actual cancellation. This adds substantial meaning beyond the bare schema.

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 starts with a clear verb+resource: 'Cancel an order belonging to a specific customer.' It immediately distinguishes from sibling tools like lookup_order and list_customer_orders by emphasizing the cancellation action and the ownership constraint, leaving no ambiguity about the tool's purpose.

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

Usage Guidelines5/5

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

Provides explicit when-to-use guidance: the order must exist, belong to customer_id, and be in a cancellable state (Pending or Processing). It also prescribes the two-step workflow (preview with confirmed=False, then confirm with confirmed=True) and clarifies that the client must handle customer authentication. This is strong, actionable 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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