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Order costs

food_order_costs
Read-onlyIdempotent

Retrieve delivery fee, ETA, minimum order, and coupon conditions for a restaurant to compare costs before recommending it.

Instructions

Get the extra costs and conditions of ordering from one restaurant.

Use before recommending a restaurant: delivery fee and ETA here, minimum order, and coupons (each with the basket total it needs and whether it is first-order only). Per-item packaging fees are in food_menu.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude of the delivery point (Iran: ~25 to ~40).
longYesLongitude of the delivery point (Iran: ~44 to ~63).
vendor_codeYesSnappfood vendor code, e.g. '947evd' (from food_search / food_restaurants).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world), so the bar is lower. The description adds real behavioral context about what the operation surfaces: delivery fee and ETA, minimum order, and coupon semantics including the required basket total and first-order-only constraints. It doesn't disclose failure modes (e.g. unsupported coordinates/vendor), but that is a minor gap given annotation coverage.

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?

Purpose is front-loaded in the first sentence, usage guidance follows, and the closing cross-reference to food_menu prevents double-fetching. Every sentence carries information; no filler.

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?

With an output schema present, return values need no explanation, and the description still summarizes the key response contents and coupon logic. It supplies usage timing and a sibling cross-reference. Slightly short of 5 only because it omits any note on error/edge conditions for out-of-range coordinates.

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 the schema fully documents vendor_code, lat, and long, including the vendor-code origin. The description adds no syntax or format detail beyond the schema, so the baseline 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?

Specific verb ('Get') plus precise resource ('the extra costs and conditions of ordering from one restaurant') with clearly enumerated scope: delivery fee, ETA, minimum order, coupons. It also distinguishes itself from the sibling food_menu by noting that per-item packaging fees live there, so an agent can tell the two apart without opening schemas.

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 restaurant' gives an explicit trigger condition, which is strong. It also names food_menu as the complementary source for packaging fees. It stops short of stating when NOT to use it or naming a full alternative for the cost-comparison task (e.g. food_find_cheapest), so it falls just short of 5.

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