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Check a shopping list

check_cart
Read-onlyIdempotent

Check a shopping or gift list: for each item, which scored company it belongs to (if any), the cited facts Shoptegrity holds (parent, filings, shareholder payouts) and what is withheld. Items can be products, brands or stores, such as 'AirPods', 'Tide pods' or 'Walmart'. Up to 50 items.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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 covered. The description adds real value beyond them by disclosing the result shape (company match, cited facts on parent/filings/payouts, and what is withheld) and a hard operational limit of 50 items.

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?

Two dense sentences with no filler; the core action is front-loaded and the item examples and 50-item limit follow immediately. Slightly packed with parenthetical detail, but nothing is wasted.

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?

An output schema exists, so return values need not be enumerated, yet the description still characterizes the per-item output. Combined with the item-type guidance and batch limit, an agent has enough to invoke it correctly; only cross-tool routing is missing.

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 coverage is 0% for the single 'items' array, so the description must carry the meaning, and it does: it defines the acceptable item types (products, brands, stores), gives concrete examples ('AirPods', 'Tide pods', 'Walmart'), and states the batch ceiling of 50. Only the array element format details are left implicit.

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?

States a specific verb and resource ('Check a shopping or gift list') and spells out what the response contains per item (scored company, cited facts, withheld data). It is clearly distinguishable in scope from siblings like check_deal or check_seller, though no sibling is named explicitly.

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?

Usage is implied rather than stated: 'Items can be products, brands or stores' plus the 50-item cap tell the agent this is a batch-resolution tool, but there is no explicit when-to-use/when-not guidance or routing to alternatives such as lookup_brand, get_brand_parent_feed or find_alternatives.

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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