Korea Ocean Leisure

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. It only lists the data returned (water temp, wave height, etc.) but does not disclose whether it is a read-only operation, how filtering by date/place works, whether pagination is involved, or the response format. This is a significant gap for a tool with no annotation coverage.

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, concise sentence that directly states the tool's purpose and the data fields it returns. It avoids unnecessary verbosity and gets to the point. However, it is not front-loaded with the most critical usage context (like how to select parameters), but for what it covers, it is appropriately sized.

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?

With 3 parameters, no output schema, and no annotations, the description should provide substantial context. It only lists data categories without explaining parameter interactions, the meaning of '종합 판정' (overall assessment), or any example usage. This is inadequate for an agent to correctly invoke the tool and interpret results.

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 only 33% (only 'place' has a description). The tool description adds no explanation for 'date' or 'limit' parameters, nor does it clarify their purpose, formats, or constraints. It completely fails to compensate for the low schema coverage, leaving agents with insufficient information to correctly fill these parameters.

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 provides a Korean beach index with specific metrics (water temperature, wave height, air temperature, open/close status, and overall assessment). It identifies the domain as 'beach' and the specific data fields, distinguishing it from sibling tools focused on fishing, surfing, etc., though it doesn't explicitly name alternatives. This is more than a tautology of the tool name.

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 gives no guidance on when to use this tool versus its siblings (korea_fishing_index, korea_surfing_index, etc.). It only describes the output content, not the context of use, selection criteria, or any exclusions. An agent would have to infer when to call this based solely on the name, which is insufficient.

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 of behavioral disclosure. It describes what data the tool returns and implies a read-only query operation ('answers' a question), but it does not explicitly state that it performs no mutations, require no authentication, or have any side effects. The absence of such explicit disclosure is a minor gap, but the nature of an 'index' tool suggests non-destructive behavior.

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 concise, two sentences, and front-loads the core purpose and key outputs. It avoids fluff and is well-structured. It could be slightly more structured by separating the purpose from the details, but it is efficient and readable.

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 is a query with four optional parameters and no output schema, the description provides a solid overview of what the result will contain (species, tides, wave, temp, wind, overall judgment, and type distinction). It does not specify the exact response format, but for a simple lookup tool this is sufficient. The absence of annotations is compensated by the clear scope and expected outputs.

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 four parameters (date, kind, limit, place) are already documented in the schema. The description does not add any additional meaning about parameter usage, formats, or relationships. It meets the baseline but does not go beyond what the schema provides.

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 ('answers where should I go fishing') and resource (Korea fishing index), and enumerates the data it provides (target species, tidal times, wave height, water temp, wind speed, overall judgment). It clearly distinguishes from sibling indexes by focusing on fishing, but it does not explicitly name an alternative or contrast with them, so it falls short of a perfect 5.

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 phrase '오늘 어디 낚시 갈만한가' (where should I go fishing today) gives an implied usage context, but the description does not state when not to use it, what alternatives exist (e.g., beach or scuba indexes), or any prerequisites. Usage guidance is present but only implicit, not explicit.

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 full burden. It explains that the tool provides start/end times, weather, wind speed, and a final recommendation based on tide conditions, giving a clear picture of behavior and output. It does not mention side effects or limitations, but for a read-only index tool this is sufficient.

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, compact sentence that covers the tool's purpose, key inputs (village, date), and output aspects (times, weather, wind, judgment). No redundant or vague wording; it is efficient and directly informative.

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?

No output schema is provided, so the description must convey what the tool returns. It mentions start/end times, weather, wind, and overall judgment, which is enough for an agent to understand the response type. It does not specify the exact format (e.g., JSON structure), but given the niche use case, this level of detail 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 descriptions cover 'date' with format and 'place' with example, but 'limit' has no description. The tool description itself adds no further clarification about parameters, especially 'limit'. With 67% schema coverage (2 of 3 parameters described), it falls in the middle; the description does not compensate for the missing 'limit' explanation.

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 it provides a mudflat experience index, including available times, weather, wind, and overall judgment based on tides. This distinguishes it from sibling tools like beach or surfing indexes by explicitly naming 'mudflat' as the subject.

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 use for mudflat-related queries but does not explicitly compare with alternatives (e.g., 'use this for mudflat, not beach'). Since it is part of a series of similar 'korea_*_index' tools, explicit guidance would help but is not provided.

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, and the description does not disclose side effects, data source, update frequency, read-only status, or any limitations. The tool appears to be a query/index operation, but this is 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, concise sentence with no redundant or irrelevant content. It efficiently communicates the tool's purpose and key data categories.

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 gives a high-level summary of output content but lacks essential context for a caller: parameter semantics, input expectations, output format, and any usage prerequisites. Without this, an agent cannot reliably invoke the 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 parameters (date, limit, place) have no descriptions, and the description only loosely implies the 'place' parameter via 'diving area'. There is no explanation of accepted formats, units, defaults, or required combinations.

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 Korea scuba index and specifies the content areas (diving area, water temperature, wave height, current speed, tide, comprehensive assessment). It is sufficiently distinct from the sibling beach/fishing/surfing indices.

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 does not state when to use this tool versus the sibling index tools, nor does it provide any conditions or scenarios for invocation. Usage must be inferred entirely from the tool name and content summary.

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 present, so the description carries the burden. It clearly indicates an informational read-only behavior ('알려준다'), with no hints of side effects or destructive actions. However, it does not explicitly confirm non-mutating or safe behavior, leaving slight ambiguity.

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, focused sentence with no redundant information. It is appropriately sized and front-loaded with the essential purpose.

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 provides core functionality but omits details on return format, required parameter combinations, or any constraints (e.g., date format, limit bounds). Given no output schema, this lack of context reduces completeness for an agent seeking to invoke the tool 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 coverage is low (only 'place' has a description, 33%). The main description does not explain 'date' or 'limit', leaving their purpose and format unclear. The description compensates partially for 'place' with an example but fails to clarify the other parameters.

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 provides sea parting index times and judgments for specific locations, distinguishing it from sibling tools focused on beach, fishing, mudflat, scuba, and surfing indexes. The verb '알려준다' (informs) is specific and resource-oriented.

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 sea parting information (e.g., Jindo and Jebudo) but does not explicitly state when to choose this tool over siblings or provide any usage conditions. It relies on domain inference rather than explicit 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?

With no annotations provided, the description must carry the full burden. It describes the output (wave height, period, etc.), which indicates what the tool returns, but it does not disclose any side effects, permissions, or safety aspects (e.g., read-only nature). The behavioral information is limited to the output content, not broader behavioral traits.

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, concise sentence that packs a lot of information without unnecessary words. It is well-structured and immediately conveys the tool's scope and key outputs.

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 gives a good overview of the output fields but lacks details on input parameters and usage context. Given that the tool is relatively simple, the description is adequate for understanding its overall function, but it leaves gaps regarding parameter meanings and any constraints, making it only partially complete.

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 description coverage is very low (only 1 out of 3 parameters has a description, i.e., 33%). The tool description does not explain the meaning of 'date', 'limit', or 'place' beyond the single hint for 'place' in the schema. Since the description does not compensate for the missing parameter explanations, parameter semantics are essentially absent.

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: it provides a surf index for Korea, detailing wave height, period, water temperature, wind, recommended skill level, and overall assessment per surf point. It explicitly mentions 'surfing' which distinguishes it from the sibling tools (beach, fishing, mudflat, scuba, seaparting).

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?

There is no explicit guidance on when to use this tool versus alternatives. The description implies it is for surf-related information, but it does not mention any conditions for selection or provide contrast with sibling tools. No 'use this when' or 'instead of' statements are present.

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 exist, so the description carries the full burden. Saying 'list' plus the explicit scope of '42 nationwide' makes it clear this is a non-mutating retrieval operation and frames its output as station identifiers suitable for another tool. Lacking explicit mention of return fields is a minor gap.

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 concise sentences with no filler. The first sentence states the resource and scope, and the second explains downstream usage.

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 optional-parameter list tool with no output schema, the description plus schema is nearly complete. It conveys the data scope and how results should be consumed, though it could more explicitly list the fields returned per station.

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 only parameter q is already fully documented in the schema as 'filter by part of name', so schema coverage is 100%. The description does not add extra semantic information about q itself; its note about the station argument relates to the output, not the parameter.

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 resource ('tidal observation stations'), the scope ('42 nationwide'), and the operation (listing them). It further distinguishes itself from siblings by noting its purpose is to feed the station argument of korea_tide_times.

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 usage context: this tool supplies the station values to korea_tide_times. It does not explicitly contrast with alternative tools, but among the siblings only korea_tide_times consumes station arguments, so the guidance is 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?

No annotations are provided, so the description carries the burden of behavioral disclosure. It communicates that the tool is a read-style lookup yielding times and tide levels, and it implies no side effects, but it does not discuss limitations, edge cases, or response format details. This is adequate but leaves room for more transparency.

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 and well-structured: the core output is front-loaded in bold, followed by relatable example questions and real-world use cases. Every sentence contributes value without repetition 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?

Given that there is no output schema, the description adequately explains what the tool returns and why it is useful. It does not specify the exact return structure or units, but for a simple tide-time lookup the level of detail is largely sufficient.

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 parameters station and date are already well documented. The description adds the context that the data is station-specific and answers 'today' questions, but it does not meaningfully enhance parameter semantics beyond what the schema already provides.

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 that the tool provides high tide and low tide times and tide levels for Korean tide stations, using specific terms like 고조(만조)·저조(간조). It is unambiguous about the resource and output, but it does not explicitly differentiate itself from sibling tools such as korea_tide_stations or the index-based 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 description gives concrete usage scenarios, such as answering 'When does the water go out?' or 'What time is high tide?', and positions the data as a basis for mudflat, fishing, and sea-separating plans. This provides clear contextual guidance, though it does not explicitly mention when not to use it or alternatives like korea_tide_stations.

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