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 behavioral burden. It conveys that this is a read-style lookup and that the identifier can be of three types, but it does not describe the response shape, potential 'not found' behavior, or whether name matching is exact or fuzzy. This is acceptable for a simple getter but leaves some uncertainty.

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 well-structured sentence front-loads the core purpose and then lists identifier options. There is no filler or redundant repetition of the title.

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 one-parameter lookup tool with no output schema, the description is nearly complete: it states what the tool retrieves, how to identify the beach, and where the id comes from. The main gap is that 'full profile' is not expanded, but this is minor given the simplicity of 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?

Schema description coverage is 100% and already explains the id_or_name parameter with examples. The description adds the useful nuance that the id is a slug coming from search results, but it largely restates what the schema provides, so a baseline score 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?

The description names a specific verb ('Get') and a precise resource ('full profile of one beach'), and distinguishes it from the sibling search tool by emphasizing a single beach rather than a list. Listing three lookup modes (slug, Wikidata Q-id, name) leaves no ambiguity about what the tool does.

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 'its slug, from search results' implicitly tells the agent to use search_beaches first to obtain the id, which is useful routing context. It does not explicitly name alternatives or state when not to use it, but the one-beach lookup purpose is clear enough.

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?

There are no annotations, so the description must carry the behavioral burden. It does disclose that results are compact and that all filters are optional/combinable, which is useful. However, it does not disclose result ordering/ranking behavior for month queries, default limits, or explicitly state that this is a read-only operation.

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 wasted words. It front-loads the core action, then adds the most decision-relevant details about filters and the get_beach 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?

With no output schema and no annotations, the tool description provides only a minimal 'compact records' hint about return shape and does not clarify how it relates to sea_temperature_year or warmest_beaches_in_month. For a tool with six parameters and specialized siblings, this leaves several selection and usage questions unanswered.

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 already documents all six parameters at 100% coverage, so the baseline is 3. The description adds value by stating that all filters are optional and combinable, a parameter-level behavior not explicitly spelled out in 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 states the tool searches and filters the beach atlas, and the title adds the worldwide scope. It explicitly contrasts itself with get_beach by noting that it returns compact records rather than full profiles. However, it does not differentiate itself from the temperature-focused siblings (sea_temperature_year, warmest_beaches_in_month), which overlap with the month and min_sea_temp_c parameters.

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 clear context: this tool is for searching/filtering when compact records are sufficient, and get_beach should be used when a full profile is needed. It does not explicitly say when to prefer the specialized temperature siblings over this tool, so exclusion guidance is incomplete.

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 full burden of behavioral disclosure. It transparently reveals the output structure: twelve monthly means and the months exceeding 20°C, including the temperature threshold. It does not discuss error handling or edge cases, but for a simple read-only query tool this is reasonable.

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. It front-loads the core output (twelve monthly means, threshold months) and then supplies the motivating question, making it easy for an agent to quickly grasp the tool's 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?

For a single-parameter tool with no output schema, the description adequately covers what the tool returns and why an agent would use it. The input schema already documents the parameter, so 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 coverage is 100%, with id_or_name fully described as 'Beach id, Wikidata Q-id or name'. The description adds minimal semantic value beyond reinforcing that the tool targets one beach, so the baseline score of 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?

The description clearly states what the tool returns: twelve monthly mean temperatures for a single beach plus the months reaching 20°C. It also frames the tool around a concrete question ('when is it warm enough there?'), which distinguishes it from siblings like warmest_beaches_in_month, which compares beaches rather than a single beach across a year.

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 the appropriate use case: checking the year-round temperature profile for one specific beach. It does not explicitly mention alternatives or exclusion conditions, but the emphasis on 'one beach' and 'whole year' gives enough contextual guidance to avoid confusion with search_beaches or warmest_beaches_in_month.

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 and discloses important behavior: ranking order, monthly mean as the basis, and the exclusion of unmeasured beaches rather than ranking them as cold. This is valuable edge-case transparency beyond 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?

Three tight sentences: the first front-loads the core ranking behavior, the second anchors user intent, and the third discloses a key edge case. Every sentence 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?

For a read-only ranked-list tool, the description covers purpose, ranking logic, and an edge case. Without an output schema, it could be more complete by noting what fields each result contains, but the overall context is strong.

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%, so the schema already documents all parameters. The description adds no meaningful parameter-level information beyond reinforcing that month and mean sea temperature are central, which is already present in 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 specifies a concrete operation: ranking beaches by mean sea temperature for a month, warmest first. The 'where can I swim in February?' question adds user intent, but the tool is not explicitly differentiated from siblings like sea_temperature_year.

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 'where can I swim in February?' framing provides a clear context for when to use this tool. It does not name alternatives or explain when not to use it, so it falls just short of full guidance.

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