snow_depth

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

With no annotations, the description carries the full disclosure burden. It states the return type and units (float in meters), the exact meaning and valid range of lead_time_swiss (2 to 121 hours from 00:00 Swiss local time), and provides multiple examples that clarify the time arithmetic. This goes well beyond minimal behavior disclosure.

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-organized with explicit Args, Returns, and Examples sections. It front-loads the core purpose, then gives parameter details and illustrative examples without repetition or filler.

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 no annotations, a bare input schema, and a simple two-parameter tool, the description provides everything an agent needs: parameter meaning, constraints, return units, and example calls. The sibling tools are different variables and require no additional disambiguation.

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 0%, so the description must fully document parameters. It explains location with an example, defines lead_time_swiss as the hour offset, provides min/max constraints, and all examples map offsets to concrete Swiss local times. Every parameter is semantically covered despite the bare 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-resource pair: 'Get forecasted snow depth for a location at a specific offset time.' It clearly distinguishes snow_depth from the sibling weather tools by naming the exact physical quantity and its temporal dimension.

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 makes clear it is for obtaining forecasted snow depth at a location and offset time, and documents the valid lead-time range. It does not explicitly compare with alternatives, but among the listed sibling weather tools, selection is straightforward from the variable name and description, so explicit exclusion is not necessary.

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