get_marine_conditions

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

With no annotations provided, the description carries the full disclosure burden. It transparently details what data is returned (wave height in meters, direction, period, swell, wind-wave parameters, hourly/daily forecasts) and the return container. It does not discuss limitations like geographic scope, update frequency, or data source, but for a read-only retrieval tool the behavioral disclosure is strong.

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 organized into clear sections (summary, examples, provides, use-case, args, returns) and is front-loaded with the core purpose. The examples and use-case list add practical context, though the content is somewhat longer than strictly necessary for an agent to invoke the tool correctly.

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 5 parameters, no schema-level descriptions, and an output schema, the description adequately covers invocation details: required and optional parameters, defaults, ranges, and returned fields. It could be more complete by stating the exact geographic coverage and any data-source caveats, but nothing essential for calling the tool is missing.

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 zero parameter descriptions, so the description's Args block provides all semantic meaning. It explains latitude and longitude in decimal degrees, gives the valid range and default for forecast_days (1-16, default 7), and clarifies the boolean and timezone defaults. This fully compensates for the sparse 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 opens with a specific verb and resource: 'Retrieves marine conditions for lakes and coastal areas,' clearly distinguishing it from general weather tools. It further specifies the data domain (wave height, swell, period, wind-wave states) and provides concrete examples, so an agent can immediately tell it apart from siblings like get_weather and get_snow_conditions.

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 'Use this tool when' section explicitly lists water sports planning, boating safety, and recreation planning on Swiss lakes, giving clear guidance on appropriate contexts. However, it does not explicitly state when not to use it or name alternative tools, so it stops short of a full 5.

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