get_lease_stores

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

No annotations are provided, so the description carries the full disclosure burden. It does disclose that the API is '실시간 REST API' (real-time) and reveals in the title that it is a read operation (get), but it omits auth requirements, pagination/large-result behavior, whether the data is volatile, and any error or empty-result semantics. For an unannotated tool this is a noticeable gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded in the first line and the paragraph is compact. The field list is useful, and the parameter section is well organized into a three-line block that mirrors the schema. Minor redundancy in repeating '필터' (filter) for each parameter, but overall every line earns its place.

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

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

An output schema exists, which relieves the description of documenting return-value structure. Combined with full parameter documentation (6.4) and the stated real-time nature, an agent has most of what it needs to invoke the tool correctly. Remaining gaps are pagination/result-volume behavior and known limitations on result count for broad queries with all parameters empty.

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

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

Schema description coverage is 0%, putting the entire burden on the description, which fully compensates. All three parameters (store_name partial match, station_code exact match, station_name exact match) are documented with match semantics and concrete examples (e.g., '파리바게뜨', '0001', '서울역'). This is exactly the value the description should add beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description states a specific verb (조회/inquiry) and resource (임대매장/lease stores within stations), and lists the fields returned (store name, location, station, headquarters, dates, hours), making it distinguishable from get_lease_codes and get_leased_assets by subject matter. The field list gives concrete substance, but it doesn't explicitly contrast against its closest siblings, so it stays below a 5.

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

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

The description explains how to use each filter (partial vs exact match) with Korean examples, which is genuine usage guidance. However, it never tells the agent when to choose this tool over get_lease_codes or get_leased_assets, nor does it state exclusions or context. Filter mechanics are covered but tool-selection context is absent.

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