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Glama

Find KFC China stores

find_stores
Read-only

Locate KFC China restaurants by keyword and city code or latitude/longitude, then use the returned storeCode to select a store for ordering.

Instructions

Find KFC China restaurants by 门店关键词 + 城市国标码 (gbCityCode, e.g. 310100 = Shanghai) or by latitude/longitude. Returns storeCode you pass to select_store. 查询肯德基门店,返回 storeCode。

Input Schema

NameRequiredDescriptionDefault
limitNo返回数量上限
keywordNo门店/地址关键词,如“淮海路”“人民广场”
cityCodeNo城市国标码 gbCityCode,例如上海 310100、北京 110100、深圳 440300
latitudeNo纬度,配合 longitude 使用
longitudeNo经度,配合 latitude 使用

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered; the description adds real value by disclosing the key output contract (storeCode) and the downstream dependency on select_store. It does not describe result shape beyond storeCode or how limit interacts with the two search modes.

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 English portion is front-loaded with the two lookup modes and the return value in two tight sentences. The trailing Chinese restatement ('查询肯德基门店,返回 storeCode') duplicates information already given, a minor redundancy rather than a structural flaw.

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 no output schema, the description correctly covers the essential return value (storeCode) and its consumer (select_store). The remaining gap is that all five parameters are optional, and the description never explains what an empty call returns or how limit defaults behave.

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% and every parameter (limit, keyword, cityCode, latitude, longitude) is already documented inline. The description's 'gbCityCode, e.g. 310100 = Shanghai' and 'latitude/longitude' pairing largely restate the schema, so this lands at the baseline 3.

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 and resource (find KFC China restaurants) and enumerates the two supported lookup modes: keyword + gbCityCode, or latitude/longitude. It also distinguishes itself from the sibling it feeds into by noting the returned storeCode is what you pass to select_store.

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?

Clear context for use: supply keyword + city code, or coordinates, and then hand the resulting storeCode to select_store — this spells out a concrete workflow. It stops short of stating when not to use it or what happens if no parameters are supplied, so it is not a full 5.

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