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

Annotations already establish that this is read-only, idempotent, and non-destructive. The description adds useful behavioral detail by specifying what the returned forecast document contains, which is valuable since there is no output schema. There is no contradiction with the annotations.

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 entire description is a single, front-loaded sentence with no filler. It states the action, resource, input source, and expected output contents efficiently.

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?

For a simple one-parameter read operation with strong annotations, the description is complete: it specifies how to obtain the id, what will be returned, and the nature of the operation. No critical information for correct invocation is missing.

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% and the schema already explains that id is a spot slug from search. The description reinforces this and adds a concrete example ('tenryuji-temple'), but it does not add substantial meaning beyond the 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 states a specific verb ('Fetch'), a clear resource ('full forecast document for one foliage spot by id'), and enumerates the document contents. It also includes a concrete slug example, making the tool's purpose unmistakable and distinct from sibling search/find tools.

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 clearly indicates the input should come from search or find_peak_spots, which tells the agent when fetch is appropriate: after a spot has been identified. It does not explicitly state when not to use it relative to get_coverage, but the single-spot-by-id framing provides sufficient context.

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