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

With no annotations, the description bears full burden. It transparently describes the output (months with sun, season span, viable days, ranking) and the shared axis capability. However, it does not explicitly state read-only nature or any authentication requirements.

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?

Two concise sentences: first sentence states purpose with example, second lists outputs and distinguishes from sibling. Every sentence earns its place, front-loaded with key information.

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 (5 parameters, comparison, no output schema), the description is quite complete: it explains purpose, outputs, and provides usage guidance. Could optionally mention read-only nature, but overall adequate.

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 coverage is 100%, so baseline is 3. The description adds minimal parameter insight beyond the schema, though the example query helps contextualize the 'places' parameter. No additional value for other parameters.

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 compares vitamin D year of 2-5 places side by side, gives an illustrative example query, and distinguishes itself from the sibling tool get_vitamin_d_year by noting that only this tool can draw years on a shared axis.

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?

Explicitly recommends using this tool instead of calling get_vitamin_d_year once per city, providing clear when-to-use guidance. The example query also helps contextualize usage.

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