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Check Mega MGC Coffee stock by region

check_mgc_stock_by_region

Check real-time sold-out status for a menu item at Mega MGC Coffee stores in a specified region using the official app API.

Instructions

Check Mega MGC Coffee app API sold_out values only for stores matching a region query. Example: 서울 종로구 or 서울 종로구 이화동 혜화동.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoCity/province token, for example 서울 or 대구.
districtNoDistrict token, for example 종로구.
itemCodeNoMega MGC app item_cd. Example: 107350.
maxStoresNoMaximum matched stores to check.
concurrencyNoConcurrent app API requests.
productNameNoMenu/product name, for example 와앙 핫 치즈스틱 & 딥.
regionQueryNoFree-form region query. Example: 서울 종로구 or 서울 종로구 이화동 혜화동.
resultLimitNoMaximum stores returned per result group.
neighborhoodsNoNeighborhood tokens matched as OR after city/district, for example ["이화동", "혜화동"].
refreshStoresNoForce refresh store cache before stock check.
storeCachePathNoCache file path. Default: data/mgc-stores.json.
storeCacheTtlHoursNoCache TTL in hours.
Behavior3/5

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

No annotations provided. The description indicates it checks sold_out values via the app API, implying a read operation, but does not disclose caching behavior, network dependencies, or potential performance implications. The parameter descriptions somewhat compensate.

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 sentences: first states purpose, second provides examples. No redundant information, front-loaded, and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 12 parameters and no output schema, the description could elaborate on return values or behavioral details like caching. However, the schema covers parameters, and the description provides useful examples, making it adequate but not thorough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds value by providing usage examples (e.g., '서울 종로구') that clarify region query format and purpose, going beyond schema definitions.

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 clearly states the tool checks sold_out values for stores matching a region query, with examples. It distinguishes from sibling tools (check_mgc_stock, check_mgc_stock_nationwide, etc.) by focusing on regional filtering.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when a region query is available but does not explicitly contrast with sibling tools or provide when-not-to-use guidance. No alternatives are named.

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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