corp_identifier

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

No annotations are provided, so the description carries the full burden of behavioral transparency. It describes the lookup chain (DART corpCode.xml → company.json → NAVER) and states that if multiple companies with the same name exist, it shows the full list. It does not explicitly state that the tool is read-only, but the nature of a lookup implies no side effects. The description provides sufficient detail on how the tool operates.

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 clear sections ('desc', 'when', 'rule', 'ref'). It is concise, containing only essential information without unnecessary words or repetition. Every section adds unique value.

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?

Given that the tool has an output schema (not shown but present), the description does not need to detail return values. It covers the lookup chain, input types, and behavior with same-name companies. The description is complete for a lookup tool with 2 parameters, though it could mention error handling for unknown queries.

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 has 2 parameters without descriptions (0% coverage). The description implies that the 'query' parameter accepts various identifiers such as stock code, company name, etc., but does not explicitly describe the 'format' parameter or its possible values. While the description adds some value beyond the schema, it could be more specific about parameter usage and options.

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 purpose: collecting all possible identifiers and classifications for a company from DART/NAVER sources. It specifies the verb '조회' (lookup) and the resource '기업 통합 식별자' (corporate integrated identifier). It distinguishes itself from siblings by being the identifier resolution tool that precedes other corporate analysis 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 'when' section explicitly states when to use this tool: with any input like stock code, company name, English name, or abbreviation to get full identifiers. It also mentions use cases like checking same-name companies or debugging matching failures. It advises running this tool before calling other tools to specify the company, referencing sibling tools as related context.

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