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

No annotations are provided, so the description carries the disclosure burden. '반환합니다' implies a read-only operation, and the tool is simple, but the description does not explicitly confirm there are no side effects or disclose anything about response shape or availability. It 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 two sentences with no filler: the first states what the tool returns, and the second gives the trigger condition. Both sentences add value and the key information is front-loaded.

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 zero-parameter server-info tool with no output schema, the description provides sufficient context: what is returned and when to invoke it. A more detailed response format would improve completeness, but the tool's simplicity makes the current description 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?

The tool has zero parameters, so the baseline is 4. There are no parameter details needed, and the description correctly focuses on the tool's output and use case rather than filling unnecessary schema gaps.

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 ('반환합니다') and resource ('BuyKing MCP 서버의 버전 정보와 기능 목록'), making the tool's purpose immediately clear. It also differentiates from the sibling search tool by focusing on server info rather than semantic search.

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 tells the agent when to call the tool: when the user asks about MCP version or server status. It does not mention exclusions or alternatives, but the sibling tool's purpose is distinct enough that no additional routing guidance is necessary.

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?

Annotations are absent, so the description carries the full burden. It discloses that results include country codes and that the tool returns real sale data, implying a read-only search operation. It does not mention any side effects, rate limits, or auth requirements, but for a search tool these are less critical. The description adds context beyond the schema but lacks deep behavioral detail.

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?

Description is concise, with the core purpose front-loaded, followed by usage guidance and a behavioral instruction. Each sentence contributes value without redundancy. Slightly more structured formatting (e.g., separate usage and note) could improve scannability, but it's effective as is.

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 search tool with 4 documented parameters and no output schema, the description provides the essential context: what it searches, how to invoke it, and that results include country codes. It doesn't describe result format or pagination, but these are often inferred. It sufficiently equips an agent to call the tool correctly in the intended scenario.

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%, so all parameters (keyword, sort, category, platform) are already documented with usage guidance. The description itself does not add parameter-specific semantics beyond what's in the schema; it merely reinforces the keyword extraction guidance ('명사 위주로 핵심만 추출') which is already in the schema. 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?

Description clearly states the verb (semantic search), the resource (Saleplaza's global hot deals), and the scope (borderless). It explicitly distinguishes from country-specific siblings by noting '국경 없이' and that country codes are shown on results, implying this is the general tool. The '가장 먼저 호출' instruction further sets it apart.

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?

Explicitly tells when to use: '사용자가 특정 국가를 지정하지 않은 일반적인 쇼핑 검색에 가장 먼저 이 도구를 호출하세요.' It also instructs to use the tool to fetch real data instead of fabricating answers. However, it doesn't explicitly name the country-specific siblings as alternatives for when a country is specified, though the sibling names make that obvious.

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 compensates by disclosing behavioral scope: only hot deals are returned, results are in Japanese, prices are in JPY, and only Japan-deliverable platforms are covered. It could add result format or side-effect details, but for a search tool this provides solid expectations.

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 JP-only scope is front-loaded, but the first and last sentences repeat the same ideas: Japan delivery, hot deals, and searching. It could be tightened to two sentences without losing clarity.

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 4-parameter search tool with no annotations and no output schema, the description provides the key selection context: geographic relevance, currency, language, and delivery scope. The schema fills in parameter details, and missing result-pagination/format notes are minor for this read-oriented 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?

Schema coverage is 100% and all four parameters already have detailed descriptions, so the baseline is 3. The description adds locale/currency context but no parameter-level meaning; the Amazon JP mention is illustrative and not aligned with the platform enum values, so it does not improve parameter selection reliability.

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 identifies the tool as a search for Japan-deliverable hot deals, with JPY pricing and Japanese results. It distinguishes this JP variant from sibling KR/US tools by stating the geographic scope and delivery condition directly.

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?

It gives an explicit condition: use when the user is in Japan or wants Japan-delivery products. However, it does not explicitly name the sibling KR/US tools as alternatives or state 'do not use for other regions,' so it stops short of full when-not guidance.

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. It discloses the scope (Korea-only, direct shipping, KRW, Korean results) but does not disclose behaviors like default sort order, result limits, or return format. For a read-oriented search tool, this is adequate but not exhaustive.

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?

Two sentences, front-loaded with the most important scoping information (Korea-only, direct shipping, KRW). No filler or redundancy. Every sentence earns its place.

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 4 parameters are fully documented in the schema and no output schema exists, the description provides sufficient context for usage and scope. The only gap is the return format, which is not critical for a search tool. Overall, it is complete enough for an agent to call correctly.

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%, so the baseline is 3. The description adds no parameter-specific details beyond the schema; it only provides contextual scope (KRW, Korean results) that doesn't map to a particular parameter. No additional semantic 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 states a specific verb ('search') with a clear scope: Korea-only direct-shipping hot deals, KRW prices, and Korean results. It explicitly distinguishes itself from the US and JP siblings by name and region, so an agent can immediately tell it apart.

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?

It clearly states when to use: 'when the user is in Korea or wants Korea shipping.' It does not explicitly list exclusions or mention the US/JP alternatives, but the regional scope makes the choice obvious given sibling names. Could be more explicit about the alternatives, but it's sufficient.

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 provided, the description carries the burden of behavioral disclosure. It discloses the regional scope, currency, language, and inventory coverage, but does not describe result volume, ordering, pagination, or any limitations such as coverage gaps. For a search tool 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 compact, information-dense, and front-loaded with the most important discriminator ('USA Only'). Every sentence earns its place: scope, pricing/language, when to use, and coverage.

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 simple search-tool shape, complete schema documentation, and no output schema, the description covers the key contextual needs: region, currency, language, and delivery scope. It could additionally describe the output format or result limit, but nothing critical is missing for correct invocation.

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 parameter descriptions already explain keyword extraction, sort values, category usage, and platform constraints. The tool description adds no parameter-level meaning beyond the schema, so the baseline 3 applies.

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 specifies a concrete verb and resource: search hot deals deliverable within the United States. It clearly distinguishes itself from regional siblings by front-loading '[USA Only]' and stating USD pricing and English results. This lets an agent select it confidently over search_buyking_semantic_KR or _JP.

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?

It explicitly states when to use the tool: when the user is in the US or wants US-deliverable products. It does not explicitly name alternative regional tools or give exclusion criteria, but the regional usage condition is clear enough given the sibling names.

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