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

No annotations are provided, so the description carries the transparency burden. It does disclose that the tool uses the 'live Open-Meteo forecast' and lists per-day output fields, which is useful. However, it does not explicitly mention that the operation is read-only, has no side effects, or clarify network/error behavior, leaving some behavioral traits implicit for a forecast tool.

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 tightly written sentences. The first sentence packs the core purpose and output summary; the second provides usage context, example questions, and the explicit sibling alternative. Every word contributes, with no redundant content.

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 lack of an output schema, the description compensates by enumerating the return fields (peak UV, cloud cover, synthesis window, minutes needed, bestDay) and by explaining the multi-day use case. The schema comprehensively covers all parameters, so the description need not repeat them. Minor gaps remain around timezone handling consequences and potential error cases, but the overall context is sufficient for an agent to select and call this tool correctly.

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?

All 9 parameters have comprehensive schema descriptions covering ranges, defaults, units, and special roles (e.g., timezone). The tool description itself adds little parameter-specific meaning beyond 'a location' and 'NEXT FEW DAYS', so the schema carries the parameter documentation burden and earns the baseline score of 3.

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 identifies the tool as a multi-day vitamin D sunshine forecast for a location, explicitly listing the computed outputs (peak UV, cloud cover, synthesis window, minutes needed, bestDay). It further distinguishes itself from the sibling get_vitamin_d_window by highlighting the multi-day scope.

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 explicit usage guidance: 'Use this for any question spanning several days', followed by concrete examples ('which day this week should I go out'). It also directly names the alternative approach and says 'instead of calling get_vitamin_d_window once per date', making the tool-choice decision unambiguous.

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