search_station

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds meaningful context beyond the schema by stating that the search is a partial match and that it aggregates results from two separate station code systems. It does not disclose potential edge cases (e.g., no matches, duplicate codes), but this is acceptable for a read-only search tool, and the two-system behavior is clearly communicated.

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 description is extremely concise: two sentences plus examples. The main purpose and scope are front-loaded in the first sentence, and the second sentence clarifies the two-system integration. No fluff or redundancy; every word contributes to usability.

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?

Given the tool has an output schema (present), the description does not need to detail return values. It covers the input semantics, the scope of the search (two systems), and provides examples. This is sufficient for an agent to invoke the tool correctly for a simple lookup operation.

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?

The input schema has a single 'name' parameter with zero schema description coverage (0%). The description fully compensates by explaining that 'name' is a station name, supports partial matching, and provides clear examples ('서울', '수서', '광명'). This gives the agent complete understanding of how to fill the parameter.

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?

The description clearly states the verb '통합 조회' (integrated search) and the resources: station code, English name, and regional headquarters, searched by station name with partial match. This distinguishes it from sibling tools like search_urban_station by specifying it covers both the next-generation ticketing and railway operation systems, making its purpose unambiguous.

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 provides clear context by specifying it searches two distinct systems (75 stations and 1255 stations) and gives three concrete examples of valid input. While it does not explicitly name alternatives or state when not to use this tool, the scope and examples make the use case evident. It could be improved by contrasting with related station-lookup tools, but it is not ambiguous.

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