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

With no annotations, the description carries the full burden of behavioral disclosure. It does disclose what information the tool provides (data source names, freshness, record counts, available fields), which gives the agent a clear sense of the output content. However, it does not explicitly state that the operation is read-only, nor does it mention any side effects or error conditions. For a metadata tool with no parameters, this is reasonably transparent 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?

The description is a single, concise sentence that front-loads the core purpose and enumerates the key metadata elements. It contains no filler or redundancy, making it highly efficient for an agent to parse.

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 tool with no output schema and no annotations, the description is fairly complete. It tells the agent exactly what kind of information is returned (data source names, freshness, record counts, fields). One could argue it could also mention the structure or how to interpret the output, but given the simplicity of the tool, the description provides sufficient context for an agent to make an informed call.

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 accepts zero parameters, and the schema reflects that with 100% coverage (an empty schema). Since there are no parameters to document, the baseline of 4 applies. The description adds no parameter-related semantics because none are needed.

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 action ('Describes') and its resource ('available data sources'), and enumerates the specific kinds of metadata it returns (freshness, record counts, available fields). This is more specific than a generic statement, though it does not explicitly differentiate itself from the sibling tools (e.g., search_vessel_registries). However, the purpose is distinct enough that an agent can infer it is for obtaining dataset metadata rather than querying records.

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 the siblings (search_vessel_registries, lookup_vessel, get_registry_stats) or when not to use it. There is no mention of prerequisites, context, or alternatives, so an agent must infer the appropriate use case from the purpose alone.

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 behavioral disclosure burden. It indicates the tool is read-only (aggregate counts) and public (no auth scaffold), but it does not disclose the output format or any limitations. The plural 'counts' hints at a structured return, yet the exact shape is absent.

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?

A single, front-loaded sentence that clearly states the tool's purpose and intended use. No superfluous information; every word 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?

For a zero-parameter tool without an output schema, the description should specify what the return value looks like. It says 'aggregate public vessel counts' but does not detail whether it returns a single number, a breakdown by category, or a summary object. This gap could lead an agent to misinterpret the response.

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?

There are zero parameters, so the schema is trivially 100% covered. The description adds no parameter-specific meaning, but none is needed. The baseline for zero-parameter tools is 4, and this description stays within that.

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 a specific action ('Aggregate public vessel counts') and its intended query type ('how many vessels' questions). The title reinforces the purpose. While it does not explicitly name sibling tools, the aggregate-count nature distinguishes it from lookup_vessel (single record), search_vessel_registries (general search), and get_dataset_metadata (metadata 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 provides clear context for when to use the tool: when the user asks about aggregate vessel counts or quantity questions. However, it gives no explicit guidance on when not to use it or alternatives to consider, leaving that to inference.

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 discloses key behaviors: normalization of registration numbers and that the response includes a web_url. It does not cover error cases or authentication requirements, which would enrich transparency, but the provided information is useful and non-obvious.

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, with the primary purpose stated up front followed by normalization details and return value. Two sentences deliver all necessary information 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?

For a simple single-parameter lookup tool, the description covers normalization and return contents. It does not explicitly address not-found behavior or response format beyond mentioning web_url, but these are minor gaps given the tool's simplicity and lack of output schema.

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% (the parameter has a description and example), giving a baseline of 3. The description adds value beyond the schema by explaining normalization (e.g., handling dashes, spaces, Latin/Cyrillic forms), which informs the agent how to format or interpret the registration_number 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 states a specific verb ('lookup') and resource ('vessel') and clarifies the exact-match behavior with normalization. It distinguishes from siblings like search_vessel_registries by emphasizing 'exact' lookup, making the tool's role 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?

The description implies when to use this tool (when you have an exact registration number, given normalization) but does not explicitly mention when not to use it or direct the agent to alternatives like search_vessel_registries for partial matches. The usage context is inferable but not stated.

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 of behavioral disclosure. It does disclose two meaningful behaviors: deterministic ordering with exact registration-number matches first, and that each result includes a web_url for ordering an official excerpt. However, it does not mention pagination behavior, rate limits, or whether the operation is strictly read-only, which could be relevant. The disclosed behaviors are useful but not comprehensive, justifying a 3.

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 zero filler. It front-loads the core purpose, then adds the ordering behavior and result link. Every sentence contributes essential information, making it an exemplary model of conciseness.

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 has 8 parameters (0 required), no output schema, and no annotations, making the description the primary source of context. It covers the basic purpose, ordering logic, and the web_url presence, but it does not explain how filters combine (e.g., AND semantics), the effect of the source parameter, or what other fields appear in results. Given the tool's complexity, the description is adequate but leaves room for interpretation, so a 3 is appropriate.

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 nothing beyond the schema's parameter documentation; it only refers generally to 'free-text query and structured filters.' It does not provide additional context on parameter interaction or format beyond what the schema already states. Therefore, the description meets the baseline but does not elevate it.

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 (search) and the exact resources (Державний судновий реєстр України and Суднова книга України), along with the search method (free-text and structured filters). It also notes the deterministic ordering and the presence of a web_url in results, making the tool's function unambiguous. However, it does not explicitly contrast with sibling tools like lookup_vessel or get_registry_stats, so it falls just short of a perfect score.

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 conveys when to use the tool (when searching by free-text or structured filters across these registries), but it does not provide explicit guidance on when not to use it or mention alternatives. For instance, it does not say that lookup_vessel should be used for exact vessel lookups. The usage context is clear but lacks explicit exclusions or comparisons, so it earns a 3.

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