get_dividend_info

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

No annotations are provided, so the description carries the behavioral disclosure burden. It discloses the data source endpoint, the scope of data (current period and two prior periods), and the specific dividend figures returned. It does not mention API key requirements or rate limits, but for a read-only retrieval tool this is adequate.

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 and front-loaded with the tool's purpose, followed by the endpoint context and a clean Args block. Every sentence and argument description adds useful information, including the Korean terms and concrete examples.

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?

For a four-parameter data retrieval tool with an output schema, the description is complete: it covers purpose, endpoint, period scope, all parameters, allowed report types, and the fields returned. An agent has enough information to select and invoke the tool correctly without opening external documentation.

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 provides only parameter names and types with 0% description coverage, but the description fully compensates by documenting every parameter: corp_code with an example, start_year/end_year formats and examples, and the allowed report_type values including 'all'. This is exemplary parameter-level guidance.

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 opens with a specific verb and resource: 'Get dividend-related figures' across a range of years, and further identifies the exact Open DART endpoint and the specific figures returned. This clearly distinguishes it from sibling tools about financial statements, shareholder status, and price data.

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 clearly indicates this tool is for dividend-related data and explains how report_type selects report filings. It does not explicitly state when not to use it or name alternative tools, but the context is strong enough that an agent can infer the appropriate use case.

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