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Glama

ue_search

Search Uber Eats by store, dish, or product name to find delivery options, matching items, and prices for the account’s current address.

Instructions

Search Uber Eats (delivers to the account's current address; works in any country Uber Eats serves). Works with store names, dishes and products. Product searches (e.g. 'Gatorade', 'ポカリスエット') return supermarkets / drugstores together with the matching items and prices.

Use this when:

  • The user asks for delivery ('点个 X' / 'order me X'). Delivery is real food and real money — don't start a delivery order on your own initiative.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo条数,默认 10
queryYes关键词(店名 / 菜名 / 商品名)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses useful behavior: delivery to the account's current address, country coverage, and that product queries surface supermarkets/drugstores with prices. It omits auth/permission requirements and rate or result-limit behavior, so it is good but not comprehensive.

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?

Front-loads the core capability, then a short conditional block. Mostly tight, though the 'real food and real money' clause is a bit of editorializing that doesn't directly help tool selection.

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 two-parameter search tool with a complete schema and no output schema, the description covers what is searched, what results look like for product queries, and when to invoke it. Missing only permission/limit behavior and explicit sibling routing.

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 coverage is 100%, so query (store/dish/product keyword) and limit (default 10) are already documented in the schema. The description restates that queries span store names, dishes and products but adds no new syntax, format or constraint detail, 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?

States a specific verb (Search) and resource (Uber Eats) plus the searchable scope: store names, dishes, products. The note that product searches return supermarkets/drugstores with matching items and prices makes the resource behavior concrete and separable from siblings like ue_store or ue_orders.

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 'Use this when' block gives an explicit triggering condition (user asks for delivery, e.g. '点个 X' / 'order me X') and a caution against initiating delivery orders autonomously. It does not name alternatives (e.g., use ue_store to browse a specific store's menu), so the routing guidance is clear but not complete.

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