commerce-ops-mcp

Diagnose order delay

diagnose_order_delay

Identify the most likely cause of an order delay by applying deterministic rules to order context, returning supporting evidence for payment issues, inventory shortages, fulfillment delays, cancellations, or no issue.

Instructions

Apply deterministic rules to an order's context to identify the most likely cause of a delay (payment issue, inventory shortage, fulfillment delay/failure, cancelled, or no issue), with supporting evidence.

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": {
      "orderId": "<orderId>"
    },
    "name": "diagnose_order_delay"
  }
}

Input Schema

Name	Required	Description	Default
`orderId`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 1, 2026

TDQS

A3.9/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that the tool uses deterministic rules and returns supporting evidence, which is valuable. However, it does not explicitly state whether it is read-only, whether it fetches the context itself, or any side effects. For a diagnostic tool, this is acceptable but not fully transparent.

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 a single, well-structured sentence that front-loads the action and provides all key details without redundancy. Every phrase earns its place, making it highly concise.

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?

The description lists the possible delay causes and mentions supporting evidence, but it does not clarify the exact input-output relationship (e.g., whether it fetches context internally) or describe the result format. Without an output schema, this ambiguity leaves room for misinterpretation, especially given the sibling get_order_context 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?

The schema has only one parameter, orderId, with 0% schema description coverage. The description mentions 'an order's context' but does not explicitly define orderId. However, the parameter name is self-explanatory, and the phrase 'to an order's context' implies its use. Thus, the description adds minimal but sufficient meaning.

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 clearly states the tool's function: applying deterministic rules to an order's context to identify the most likely cause of a delay. It enumerates the possible outcomes (payment issue, inventory shortage, fulfillment delay/failure, cancelled, or no issue) and mentions supporting evidence, which distinguishes it from sibling tools like get_order_context that merely retrieve context.

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

Usage Guidelines4/5

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

The description implies usage when an order is delayed and the user needs to determine the cause. It does not explicitly state when not to use it or compare to alternatives, but the context is clear enough for an agent to select this tool over search_orders or recommend_resolution.

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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