Typical Weather On Any Date

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description does add genuinely useful methodology context (ERA5 2021–2025, median of 35 archive days, date ±3 days over five years) and the 'climate not forecast' caveat that a naive agent would otherwise miss. It stops short of describing response shape or any limits, but the data-provenance caveat is the main behavioral risk here and is disclosed.

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 the core purpose and the 'climate, not a forecast' distinction, then usage routing. The opening sentence is very dense with a long clause list of returned quantities, but each element is informative and no sentence is filler.

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?

An output schema exists, so return values need no explanation; the description covers provenance, the climate-vs-forecast caveat, the date/omit-date decision, the city-vs-coordinates decision, and the sibling boundary. Nothing an agent needs to select or call this correctly 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 documents lat/lng vs city, the MM-DD / YYYY-MM-DD pattern with year-ignored, and the locale fallback. The description mostly reiterates this (omit date → month overview, city vs point), adding little syntax the schema does not already carry. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific resource (typical weather / climate normals) with explicit scope: city or any lat/lng point, on a given day of the year, from a named archive. It explicitly names the sibling it is not (get_city_travel_weather) and marks the boundary ('Climate, not a forecast'), so an agent can route between the two without opening either schema.

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?

Gives explicit when-to-use ('dates beyond the coming week', 'when is the best time to go'), explicit when-not ('for today and this week use get_city_travel_weather'), plus concrete example queries. It also states the omit-date behavior, so the parameter-level decision is guided too.

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