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

Beyond the annotations (which only establish a safe, idempotent read), the description discloses methodology and caveats: daily new snow is the positive change in station depth and is 'a floor on what fell', powder days use the 8-inch alert threshold, and baselineNote appears when the 30-winter and decade normals disagree by more than 10%. This is exactly the behavioral context an agent needs to interpret the numbers honestly.

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?

Front-loaded with what it returns and packed densely; the long enumerative sentence is justified by the many distinct metrics, and the usage sentence is short. It is a run-on, but virtually every clause carries information, so little is wasted.

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?

Although an output schema exists and return values could be left to it, the description goes further and explains metric definitions, comparison baselines, and the trend/quotable sentence, which is complete for a single-resort read tool with all safety traits already covered by annotations.

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?

There is a single slug parameter and schema coverage is 100%, with the schema itself documenting the format and pointing to search_resorts. The description adds no additional parameter meaning, so the baseline of 3 applies.

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 the exact resource ('Season-to-date for one resort'), the data source ('PeakCam's own daily station record'), and enumerates the specific metrics returned, so an agent knows precisely what it retrieves. It does not, however, explicitly differentiate itself from close siblings such as get_snow_history, get_percent_of_normal, or get_monthly_climatology, leaving the agent to infer the boundary.

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 gives concrete trigger questions ('how is the season going', 'is this a good year', 'how does it compare with last year') that map cleanly to intent. It stops short of naming alternatives or exclusions, so the routing against get_percent_of_normal / get_snow_history is not spelled out.

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