Beachmap — Europe Beach Data

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

No annotations are provided, so the description carries the transparency burden. It discloses the ordering (warmest sea first) and the inclusion criterion (best-time window includes month), which adds behavioral context. However, it doesn't elaborate on potential limitations such as missing best-month data, result coverage, or whether the month uses calendar vs. seasonal definitions.

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 concise sentences: the first states the tool's behavior, the second provides a practical usage example. Every word earns its place, and 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?

The tool is a straightforward list query with a well-defined purpose and order, and the schema covers parameters. However, without an output schema or annotations, the description could further specify the return format (e.g., a list of beach objects) and any default limiting behavior, though the example and title suffice for most cases.

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 already documents all three parameters with 100% coverage, so the description doesn't need to repeat them. It adds a mild example of month usage ('October') but doesn't enrich limit or country semantics beyond the schema.

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's function: returning beaches whose best-time window includes a specified month, sorted by warmest sea temperature. It differentiates from sibling tools by the month-based seasonal filter and warm-sea ordering, and provides a concrete use case.

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 a clear example of when to use it ('where should I go in October?'), implying a seasonal search context. However, it doesn't explicitly mention when not to use it or name alternatives like warmest_beaches or search_beaches.

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 only says 'full profile' without detailing what that includes (e.g., amenities, photos, ratings), or any side effects, errors, or access requirements. This lacks depth for a read operation, though the 'get' semantics imply it is non-mutating.

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 one short sentence that packs essential information: the action (full profile), the target (one beach), and the acceptable identifiers (id or name). Every word is useful, and the structure is front-loaded and easy 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?

Given the simplicity (one param, no output schema, no annotations), the description is minimally adequate but leaves gaps. It doesn't explain what 'full profile' entails operationally—such as whether it returns all attributes, is faster than other endpoints, or has any limitations. For a simple lookup tool this may be sufficient, but more detail would make it 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?

Schema description coverage is 100% for the single parameter, which already explains 'id_or_name' with examples. The tool description adds minimal extra context by noting the id comes from search results, reinforcing what the schema says but not significantly enhancing meaning beyond the structured field.

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: retrieving the full profile of one beach. It identifies the resource (beach) and the verb (get), and distinguishes itself from sibling tools like search_beaches (which searches) and beaches_best_in_month (which lists by month) by specifying this is for a single beach profile.

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 a usage context by saying 'by id (from search results)' which implies a workflow: use search_beaches first to obtain an id, then call get_beach for the full profile. It doesn't explicitly state when not to use it, but the context is clear enough for an agent to choose appropriately.

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. It discloses that results are compact records and directs to get_beach for full profiles. The read-only nature is implied by 'search/filter', and the 'all filters optional' note clarifies that an empty call is valid. It does not mention pagination or result limits, but that is covered in the schema.

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 short sentences, front-loaded with verb and resource, with no redundant information. The pointer to get_beach earns its place by clarifying the return format and alternative.

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 tool with 8 optional parameters and no output schema, the description conveys the domain (511 beaches), result granularity (compact), and relationship to get_beach. It does not need to detail return fields since it directs to the full-profile sibling.

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 only says that filters are optional and combinable, which is a group-level note and adds no per-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 uses specific verbs ('Search and filter') and a countable resource ('511 top European beaches'), making the tool's scope immediately clear. It distinguishes itself from siblings by noting it returns compact records and that get_beach is the full-profile counterpart.

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?

States that all filters are optional and combinable, which tells the agent that any parameter combination (including none) is allowed. It also points to get_beach as an alternative for full profiles, though it does not explicitly mention when to prefer beaches_best_in_month or warmest_beaches.

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 the ranking order and filtering options, but does not mention return format, default behavior when no matches, or data source. This is adequate but leaves some behavioral aspects unstated.

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 concise sentences, front-loaded with the core purpose and followed by filter options. Every word earns its place, with no 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?

The tool is a simple list with three optional parameters and no output schema. The description explains the ranking and filtering but does not describe what the response includes (e.g., beach names, temperatures), which is a gap given no output schema exists. Adequate for a simple tool but not 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?

Schema description coverage is 100%, so the schema already documents each parameter. The description's mention of filtering by country/month adds little beyond what the schema says, though it reinforces that these are optional filters. No syntax or format details are added.

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 ranks European beaches by typical warm-season sea temperature, warmest first. This gives a specific verb (ranked), resource (European beaches), and a distinguishing scope (warmth), separating it from siblings that focus on 'best' or general 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?

It explicitly mentions optional filtering by country and/or month, providing clear context on how to narrow results. However, it does not explicitly mention when to choose this over sibling tools like beaches_best_in_month, so exclusions are absent.

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