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

Beyond the read-only annotation, the description details complex behavioral traits. It explains exactly what the default 'research' view returns (source URL, unit, date, caution points) and provides crucial operational caveats, such as how the US Treasury data parameters are narrowly interpreted.

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 highly dense and very long, which compromises ideal conciseness. However, given the extreme complexity of the domain (financial data, specialized search modes), every sentence delivers critical, non-redundant information.

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 definition is exceptionally complete for a high-complexity, zero-documentation tool. It covers scope, default returns, conditional logic, parameter interpretation, and explicit limitations, leaving few unknowns for an AI agent.

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?

Given the schema description coverage is 0%, the description carries a massive burden. It successfully compensates by explaining the semantic differences between parameters, specifically detailing the interpretation of financial terms and date formats (e.g., '명시 월(YYYY-MM/한국어 연월)'), and clarifying the distinct roles of `view:research` versus `view:catalog`.

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 function: searching for registered sources using site names or short keywords. By focusing on '등록 출처' (registered sources), it precisely scopes the action and differentiates it from generic, unindexed search tools.

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 extensive conditional guidance. It instructs the agent on specific behaviors based on the 'view' parameter, dictates how to proceed if 'request.status:unresolved,' and explicitly advises utilizing 'get_access_plan' when 'nextAction:read_original' is relevant. It also states a clear limitation: it is not for guaranteed completion or raw data retrieval.

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