find_weather_station

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 states the tool returns a list of stations with name, ID, and distance, which is helpful. However, it doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, error conditions, or data freshness. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 and well-structured, using two clear sentences that efficiently convey the tool's purpose and output. It avoids unnecessary details and is front-loaded with the main action. However, it could be slightly more polished in English translation (e.g., 'Nächstgelegene' as 'nearest'), but this doesn't significantly impact clarity.

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's moderate complexity (one parameter, no annotations, but with an output schema), the description is adequate but incomplete. It explains the output format (list with name, ID, distance), which is good since an output schema exists. However, it lacks details on usage context, parameter specifics, and behavioral traits, making it minimally viable but with clear gaps for effective tool selection.

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 0%, with one parameter ('location') undocumented in the schema. The description implies the parameter is a location for finding nearby stations but doesn't specify format (e.g., coordinates, city name) or constraints. It adds some semantic context ('specified location') but doesn't fully compensate for the lack of schema documentation, aligning with the baseline for minimal parameter info.

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: 'find nearest DWD weather stations' and 'returns a list of weather stations near the specified location'. It uses specific verbs ('find', 'returns') and identifies the resource ('DWD weather stations'). However, it doesn't explicitly differentiate from sibling tools like 'get_current_weather' or 'get_weather_forecast', which prevents a score of 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 description provides no guidance on when to use this tool versus alternatives like 'get_current_weather' or 'get_weather_forecast'. It mentions what the tool does but offers no context about use cases, prerequisites, or exclusions. This lack of comparative guidance limits its utility for an AI agent in selecting the right tool.

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