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 disclosure. While it indicates this is a read operation ('조회합니다'), it doesn't describe potential behaviors like rate limits, error conditions, authentication needs, or what happens with invalid symbols. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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, efficient sentence in Korean that directly states the tool's function without unnecessary words. It's appropriately sized for a simple price lookup tool and front-loads the essential information (action, resource, source, currency).

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 tool's low complexity (one optional parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks behavioral details and usage context. Without annotations or output schema, the agent must rely on the description alone, which is incomplete for fully informed tool selection.

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 100% description coverage, with the 'symbol' parameter clearly documented in the schema itself. The description doesn't add any parameter-specific information beyond what's in the schema. According to guidelines, when schema coverage is high (>80%), the baseline score is 3 even without parameter details in the description.

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: '조회합니다' (retrieves/checks) the KRW price of a specific cryptocurrency from Bithumb. It specifies the resource (cryptocurrency price), source (Bithumb), and currency (KRW). However, it doesn't explicitly distinguish this from sibling tools like 'get_exchange_rate' or 'get_kimp' which likely serve different financial data purposes.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools, suggest scenarios for its use, or indicate any prerequisites or exclusions. The agent must infer usage from the purpose alone without explicit context.

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 full burden. It discloses the data source (Naver) and that it retrieves current rates, but doesn't mention potential limitations like rate limits, authentication requirements, data freshness guarantees, or error conditions. For a read-only tool with no parameters, this provides basic behavioral context but lacks important operational details.

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, efficient Korean sentence that front-loads all essential information: source (Naver), action (retrieve), resource (USD/KRW exchange rate), and temporal aspect (current). Every word earns its place with zero redundancy or unnecessary elaboration.

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, parameterless tool with no output schema, the description provides the core purpose and source. However, it lacks information about return format (what structure/units the rate comes in), potential error cases, or any special considerations for using Naver as a source. The description is minimally adequate but leaves gaps an agent would need to discover through trial.

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 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema already fully documents the empty parameter structure. No additional parameter information is needed or provided.

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 specific action ('조회합니다' - retrieves/checks) and resource ('USD/KRW 환율' - USD/KRW exchange rate) from a specific source ('Naver에서' - from Naver). It distinguishes from siblings by specifying it's for traditional currency exchange rates rather than cryptocurrency prices (get_crypto_price) or kimchi premium calculations (get_kimp).

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 context by specifying '현재' (current) exchange rates from Naver, suggesting this is for real-time rate checking. However, it doesn't explicitly state when NOT to use this tool or provide clear alternatives beyond what can be inferred from sibling tool names. The context is clear but lacks explicit exclusion 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 mentions real-time calculation ('실시간 김프를 계산합니다') but lacks details on rate limits, error handling, authentication needs, or what the output format looks like. For a tool with no annotation coverage, this leaves significant behavioral gaps.

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 appropriately sized with three concise sentences. It's front-loaded with the core purpose, followed by implementation details and usage examples. Every sentence adds value without 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 tool's moderate complexity (calculating KIMP using multiple data sources), no annotations, and no output schema, the description is somewhat complete but lacks details on output format, error conditions, and behavioral constraints. It covers the what and how but not the full operational context.

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 schema already documents the single parameter 'symbol' with examples. The description adds value by clarifying that the tool works with stablecoins like USDT and USDC, which helps interpret the parameter's purpose beyond the schema's basic description.

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 specific verbs ('계산합니다', '확인할 수 있습니다') and resources ('김치 프리미엄(KIMP)', 'Bithumb의 KRW 가격', 'Naver 환율 정보', 'USDT, USDC 같은 스테이블코인'). It distinguishes from sibling tools by focusing on KIMP calculation rather than general price or exchange rate retrieval.

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 context by mentioning specific data sources (Bithumb, Naver) and cryptocurrency types (stablecoins like USDT, USDC). However, it doesn't explicitly state when to use this tool versus alternatives like get_crypto_price or get_exchange_rate, nor does it provide exclusion criteria.

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