clover-mcp

get_top_items

Read-only

Identify top-selling products by units sold in a given date range, defaulting to today. Use to analyze sales performance and optimize inventory.

Instructions

Return the best-selling items in a date window, ranked by units sold.

Defaults to today (UTC); 90-day chunked. Each line item counts as one unit. Requires ORDERS_R.

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": "get_top_items"
  }
}

Input Schema

Name	Required	Description	Default
`top_n`	No
`date_to`	No
`date_from`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.7.0Aug 7, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the bar is lower. The description adds meaningful behavioral context: default to today UTC, 90-day chunking, each line item counting as one unit, and the ORDERS_R permission requirement. This goes beyond the annotations and helps the agent understand side effects and constraints.

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 three sentences long, front-loaded with the primary purpose, and every subsequent sentence adds value (defaults, chunking, unit definition, permission). There is no fluff or repetition of schema details.

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?

Given the presence of an output schema and read-only annotations, the description adequately covers the main behavioral aspects: what the tool returns, default date window, chunking behavior, unit semantics, and required permission. The only minor gap is the ambiguous meaning of '90-day chunked' and lack of date format details, but these are not critical given the output schema.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for the three undocumented parameters. It only vaguely mentions 'date window' and default today, and does not explain the date format, inclusivity, or the meaning/constraints of top_n beyond its name. This is insufficient for an agent to confidently construct valid arguments.

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 a specific verb ('Return') with a clear resource ('best-selling items') and unique scope ('in a date window, ranked by units sold'). It clearly differentiates from sibling tools like get_sales_summary or list_orders by focusing on best-seller ranking.

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?

The description implies the tool should be used when best-selling items in a date window are needed, and it provides context like defaulting to today and requiring ORDERS_R. However, it does not explicitly state when not to use it or name alternative tools for similar analytics needs.

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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