get_ktx_long_term_stats

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

With no annotations, the description carries the behavioral burden. It discloses that data comes from a local XLSX file, explains partial matching for route, and defines the default behavior of returning all categories when category is empty. However, it does not mention performance, authentication, or error handling, leaving some transparency gaps.

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 well-structured with a header, scope statement, and bullet-point-like list for category values, followed by concise explanations for route and years. It is front-loaded with the purpose and avoids redundancy, though it could be slightly tighter by combining the year filter explanation.

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?

The description covers all parameters and data scope, and the output schema exists, so return format is not needed. However, it leaves a gap: the defaults for year_from/year_to are ambiguous—the schema defaults to 0, but the description does not explicitly state that an empty or zero value means 'all years' (unlike category and route where it clearly states empty means all). This is a notable missing detail for an agent to use the tool correctly.

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%, so the description fully compensates. It explains every parameter: category with four specific values and a default of returning all, route with partial match and default of all, and year_from/year_to with an example range. This adds substantial meaning beyond the bare schema types and defaults.

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 retrieves KTX long-term statistics (2004-2023) for two specific routes, with a clear verb ('조회' = query) and resource. It distinguishes from sibling tools by being KTX-specific and long-term, and lists the exact data categories and data source (local XLSX).

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 implies usage (for querying KTX long-term stats) but does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions. While the tool's specificity makes the choice obvious, there is no guidance on when not to use it or which sibling might be more appropriate for other statistics.

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