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

Annotations already mark it read-only, idempotent, and non-destructive. The description adds the expected disclosure content—what fields are returned, that it takes no arguments, and that it yields a citable as_of date—so the agent knows what behavior to expect beyond the safety hints.

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?

Three sentences and two example prompts with no filler. The scoping information is front-loaded, usage guidance comes next, and examples close it out; every clause earns its place.

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 zero-argument metadata tool with no output schema, the description lists all relevant output dimensions, states when to call it, and shows example invocations. An agent can select and interpret this tool without further information.

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 are no parameters; the schema is empty and coverage is 100%. The description explicitly confirms 'Takes no arguments', satisfying the baseline for a zero-parameter tool.

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 'Describe what the RoamTime Japan autumn-foliage forecast covers'—a specific verb and resource—and enumerates the exact metadata fields (forecast year, issue date, season span, regions/prefectures, spot count, access tier). This clearly distinguishes it as the coverage/orientation tool from siblings like find_peak_spots and search.

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 instructs agents to 'Call this first to orient yourself' and gives concrete trigger conditions: check whether a place/date is in scope and learn the as_of date to cite. It doesn't name exclusions or alternatives, but the 'first' guidance and scope-checking purpose are clear.

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