govdata-korea

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It does not mention that this is a read-only lookup, nor does it describe the return format or behavior when no parameters are supplied. The minimal text leaves key behavioral aspects unspecified.

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 a single, front-loaded sentence that precisely states the tool's purpose without any unnecessary words. It is appropriately sized for the simplicity of the operation.

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 tool is a simple lookup with two optional parameters and no output schema. The description is minimal but does not explain the response structure or edge-case behavior (e.g., omitting parameters, search behavior). It is adequate but lacks the detail that would make it genuinely helpful for an agent deciding whether the output fits a use case.

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 100% coverage of both parameters ('code' and 'search') with meaningful descriptions. The tool description adds no extra parameter semantics, so the baseline score of 3 is appropriate.

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 action ('Look up') and specific resource ('Korean Standard Industrial Classification (KSIC) business type codes'). It is unambiguous and distinctly different from sibling tools that handle economic indicators, exchange rates, holidays, population, or postal codes.

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 when to use the tool (whenever KSIC business type codes are needed) but provides no explicit guidance on when not to use it or alternatives. Since it is a standalone lookup tool, the context is clear enough to infer usage.

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

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

With no annotations, the description carries the burden of behavioral disclosure. It does not mention what the response looks like, whether all indicators are returned together, if the data is historical or current, or any special behavior like formatting. It only lists the indicators, leaving significant behavioral unknowns for the agent.

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 a single sentence that efficiently conveys the purpose and scope. It is front-loaded with the verb 'Get' and the resource, followed by a specific enumeration. No redundant words or phrases.

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?

This is a simple tool with one optional parameter and no output schema. The description provides enough to understand the general purpose, but it lacks context on return structure, update frequency, or how it relates to the sibling get_exchange_rates. For a tool of this simplicity, the gap is moderate.

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 schema covers the single optional parameter fully, including a list of valid values and the default behavior when omitted. The description's mention of indicator names adds little beyond the schema. Since schema coverage is 100% and the description doesn't add extra parameter details, a baseline of 3 is appropriate.

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 function: 'Get Korean economic indicators' and provides a specific list of indicators. This distinguishes it from most sibling tools like get_population and get_holidays, though it overlaps with get_exchange_rates which is a sibling. Still, the verb and resource are clear.

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?

No guidance is provided on when to use this tool versus alternatives. For instance, since get_exchange_rates exists as a sibling, it would be helpful to note whether to use this tool or that one for exchange rate data. The description only states what it does, not when to choose it.

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

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It does not state whether the tool reads live data, requires authentication, has rate limits, or how it behaves with an invalid currency code. It only states the basic action, leaving significant behavioral context undisclosed for an unannotated tool.

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 two short sentences, front-loaded with the core purpose and then the optional parameter. Every word earns its place; there is no redundancy or filler.

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 simple, one-optional-parameter lookup tool with no output schema, the description covers the essential purpose and filtering behavior. It lacks deeper context like return format or frequency, but the simplicity limits the need. Given no annotations, a score of 4 reflects that it is nearly complete for its scope.

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 schema already provides 100% coverage for the single parameter 'currency', including the example values and omission behavior. The description adds no additional semantic detail beyond what the schema states, so baseline 3 is appropriate.

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 'Get KRW exchange rates against major currencies', using a specific verb and resource that distinguishes it from sibling tools like get_economic_indicators or get_holidays. The optional filter for currency code adds precision without ambiguity.

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 when to use this tool: whenever KRW exchange rates are needed, with optional currency filtering. Sibling tools cover other domains (business types, economic indicators, holidays, population, postal codes), so the context is clear, though no explicit exclusions or alternative tool references are given.

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

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

With no annotations, the description must carry the full behavioral burden. It discloses the year-range constraint (2024-2026), which is useful. However, it does not mention return format, invalid input handling, or confirm that this is a read-only operation. For a simple GET, this is adequate but not rich.

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 a single, front-loaded sentence that efficiently conveys the tool's purpose and constraint with zero filler or redundancy.

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 the very low complexity (one optional parameter) and lack of an output schema, the description sufficiently communicates what the tool returns conceptually (Korean holidays for a year). It could mention the output structure, but for a simple lookup against sibling tools of similar nature, the context is adequate.

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 100%, and the 'year' parameter already has a detailed description in the schema ('Year (2024, 2025, or 2026). Default 2026.'). The tool description adds no additional semantic detail beyond repeating the supported years, so it meets the baseline but adds no extra value.

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 uses a specific verb 'Get' with a clear resource 'Korean public holidays' and scoping 'for a given year (2024-2026)'. It distinguishes from sibling data-lookup tools like get_exchange_rates and get_population by naming a unique domain.

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 clear context that the tool is for grabbing Korean holidays for a specific year, which implies use when holiday data is needed. It does not explicitly state alternatives or exclusions, but the sibling tools are topically distinct enough that no confusion arises.

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

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

With no annotations, the description carries the burden of disclosing behavior. It mentions the 2024 KOSIS data source, which adds context about data recency. However, it does not describe the return format, whether population is broken down by age/gender, or any limitations. Basic read-only behavior is implied but not explicitly stated.

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 a single, clear sentence that immediately conveys the tool's purpose and data source. It is concise and front-loaded with relevant information, with no wasted words.

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 tool is simple (one optional parameter) and the description provides essential context (data source, region specificity). While there is no output schema, the description and tool name sufficiently convey the general output. The absence of more detail on return structure is a minor gap but not critical for a straightforward data retrieval tool.

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 schema fully documents the 'region' parameter with examples and the default behavior ('Omit for all regions'). The description adds no additional parameter meaning beyond what the schema already provides, so a baseline of 3 is appropriate.

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 South Korea population data by region, using a specific verb ('Get') and resource ('population data'). It distinguishes itself from sibling tools like get_economic_indicators and get_business_types, which target other data types.

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 population-related queries and clearly identifies the geographic scope. However, it does not explicitly state when to use this tool over alternatives or mention exclusion criteria, though the purpose is so specific that guidance is effectively conveyed.

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

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

No annotations are provided, placing full burden on the description. While 'look up' implies a read-only operation, the description does not explicitly state safety, return behavior, or limitations. It provides only the core purpose without additional behavioral context.

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 a single, dense sentence that front-loads the verb and resource, with no unnecessary filler. Every word contributes to understanding the tool's core function.

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 simple one-parameter lookup tool, the description provides enough context to understand purpose and input format. While there is no output schema, the implicit return of postal codes is clear from the description, though explicit mention of return values would improve it.

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 fully documents the single parameter with a clear description and examples, achieving 100% schema coverage. The tool description's mention of 'district, city, area name, or postal code number' adds minimal value beyond what the schema already states, so the baseline of 3 is appropriate.

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 with a specific verb ('look up') and resource ('Korean postal codes'), and enumerates the types of query inputs. This distinguishes it from the sibling 'get_' tools which retrieve different data categories.

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 implicitly signals when to use this tool (when a Korean postal code is needed), and the sibling tools are clearly distinct in function. However, it does not explicitly mention when not to use it or present alternatives, so it stops short of a 5.

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