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

Annotations already declare readOnlyHint and openWorldHint, so the description does not need to restate safety. It adds valuable behavior not in the annotations: matching priority, stock_code being null for unlisted companies, the ~90k unlisted entity scope, and error/edge-case behavior including no-match returning count 0. This exceeds baseline transparency without contradicting the annotations.

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?

Although the description is lengthy, every section earns its place: Args, Returns, Match priority, Examples, Use-when, and Errors. The structure is scannable with clear labels, and the most important scoping information is front-loaded in the first sentence.

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 is complete for an agent to invoke the tool correctly: it covers input formats, output shape, match disambiguation, example usage, sibling routing, and error behavior. The presence of an output schema does not leave any critical gap, and the listed_only behavior is fully explained.

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 coverage is 100%, so the parameters are already documented. The description goes beyond the schema by clarifying that query accepts a name, 6-digit KRX stock code, or 8-digit corp_code, that Korean names work best, that unlisted results have null stock_code, and that match priority favors exact codes. This adds real semantic value to the agent's understanding.

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 states a specific verb ('Search') and resource ('companies registered with DART, South Korea's corporate disclosure system'), and clearly distinguishes its search identity from the US-focused sibling search_edgar_company. It also explains the tool's key output, the corp_code required by other dart_* tools, making its role in the tool family immediately obvious.

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 explicitly says when to use the tool ('when you need a corp_code or must disambiguate similar names'), and when not to use it ('Don't use for US companies (use search_edgar_company)'). It also gives practical guidance on query forms, listing scope, and match priority, leaving no ambiguity about invocation context.

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