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Remember a Grocery Choice

remember_product
Idempotent

Save a product with optional quality or quantity to remember a shopper's preference, turning stated choices into future suggestions. This action records user intent without approving purchases.

Instructions

Save a product and optional quality or usual quantity only when the user asks to remember their preference. It is a future suggestion, never purchase approval.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
labelYes
qualityNo
quantityNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.1.1

TDQS

A4/5.0
Behavior3/5

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

Annotations already indicate this is not read-only, is idempotent, and is not destructive. The description adds the conceptual behavior that saving is a suggestion rather than a purchase action, but does not explain what happens on repeated saves, whether existing memories are overwritten, or how the stored data is later used.

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?

Two short sentences convey the core purpose, optional parameters, usage condition, and a key boundary. There is no redundant wording, and the most important information is front-loaded.

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?

For a simple save-to-memory tool, the description covers what to do, when to do it, and what not to overinterpret. It leaves some parameter semantics and idempotency details implicit, but the annotations and output schema fill part of that gap, and the tool is not highly complex.

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?

Schema description coverage is 0%, so the description must compensate for missing parameter explanations. It clarifies that quality and quantity are optional preference details, but it does not define the roles of label and url beyond calling them a 'product', nor does it explain the meaning of quantity bounds or how these values interact with shopping memory.

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 states a specific action ('Save a product') with a clear resource and scope, and adds an important boundary: it is a future suggestion, never purchase approval. This clearly differentiates it from purchase-related siblings like add_to_cart and place_order.

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 explicitly limits use to when the user asks to remember their preference and warns against interpreting it as purchase approval. It does not name alternative tools explicitly, but the 'only when' phrasing provides clear usage 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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