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Glama

Grocery store details

market_store_info
Read-onlyIdempotent

Retrieve a store's delivery fee, minimum order, opening hours, rating and coupons for a delivery point, helping agents confirm the true basket cost before recommending it.

Instructions

Get one store's delivery fee, minimum order, opening hours, rating and coupons for the point.

Use before recommending a store to know the true cost of a basket: sum(final prices) + delivery_fee - applicable coupon, and the basket must reach min_order. Read each coupon's conditions; isApplicable is false for logged-out users.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude of the delivery point (Iran: ~25 to ~40).
longYesLongitude of the delivery point (Iran: ~44 to ~63).
vendor_codeYesStore code from market_search / market_stores, e.g. '32xxwe'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive), so the bar is lower, yet the description adds real behavioral context: the true-cost formula, the min_order requirement, and the logged-out caveat that 'isApplicable is false for logged-out users.' That logged-out behavior is a genuinely useful disclosure not present in the structured fields.

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?

The purpose is front-loaded in the first sentence, followed by the practical cost formula and a caveat. It is compact and every line earns its place, though the multi-line formula fragment is slightly less tidy than a single clean paragraph.

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 explained; the description covers purpose, when to use, the cost calculation, and a key behavioral caveat. Complete for an agent to call it correctly, with only minor room for naming alternatives.

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 100%, so lat, long, and vendor_code are already fully documented in the schema, including ranges and the vendor_code pattern. The description adds no parameter-level syntax or format detail beyond the schema, so the baseline of 3 applies.

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?

States a specific verb ('Get') and resource ('one store's delivery fee, minimum order, opening hours, rating and coupons'), and the enumerations make the returned scope concrete. The 'one store's' framing distinguishes it from list-oriented siblings like market_stores and market_search without needing to name them.

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?

'Use before recommending a store to know the true cost of a basket' gives an explicit usage context, reinforced by the cost formula and the min_order constraint. It stops short of naming alternative tools or stating when-not to use it, so it is clear context without full routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.