Search Seoul hotspot places

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 reveals that the tool maps to a fixed set of 121 official real-time hotspots, implying a constrained resolution rather than a general search. However, it does not describe what happens on no match, the output format, or any other behavioral edge cases, leaving a significant 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 description is concise and front-loaded, with the key purpose clear in the first sentence. However, it includes a bilingual repetition of the same message in Korean, which adds length without new information. A single-language description would have been more efficient, so not every sentence 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?

This is a simple one-parameter tool with no annotations and no output schema, so the description needs to cover core behavior and return expectations. It correctly explains the purpose and scope (matching to 121 hotspots) and gives usage guidance, but it lacks any description of the return value or failure behavior. Given the absence of an output schema, this is a meaningful gap, though the tool is simple enough that the description is not fatally inadequate.

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 schema already documents the 'query' parameter with examples (100% coverage), so the baseline is 3. The description adds semantic value by characterizing the input as 'free-form place name' and '자연어 장소명' (natural language place name), clarifying that it accepts natural language phrasing rather than structured identifiers. This goes beyond the schema's mere label.

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 tool's function: 'Resolve a free-form place name to one of Seoul's 121 official real-time hotspots.' This specifies a concrete verb ('Resolve') and a well-defined resource (Seoul's 121 official hotspots), distinguishing it from the many data-fetching sibling tools like get_subway_arrivals or get_weather.

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 explicit usage guidance: 'Use FIRST when the user mentions a Seoul location.' This tells the agent exactly when to invoke this tool, but it does not name specific alternative tools or state when not to use it, so it stops short of the full 'when/when-not/alternatives' criterion.

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