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

Annotations already cover read-only/idempotent safety, and the description adds substantial context on top: exact return contents (latest station observation, next 12 hourly periods, 6-period forecast, active alerts as normalized JSON), the 400 error shape, and the paid x402 flow including how to retry with params._meta["x402/payment"] and the plain-HTTP equivalent. This is precisely the payment/auth behavior an agent cannot infer from structured fields.

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 purpose, then usefulness, then return payload, then errors and payment details. Every sentence carries distinct information with no repetition of the title or annotations.

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 two-parameter read tool with no output schema, the description covers return contents, error behavior, cost, and transport. The only material omission is coordinate conventions and range/validation for lat/lon, which an agent needs to construct a valid call.

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 description coverage is 0% for both parameters, so the description must carry the burden. It says the coordinates must identify a US location, which is meaningful constraint information, but adds no format details such as decimal degrees, WGS84, or valid ranges, leaving lat/lon semantics largely as stated in the names.

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 verb/resource combination: current conditions, forecast and severe-weather alerts for a lat/lon from NWS, all in one call. The scope (US locations only) and the upstream source are named, so an agent can tell what it retrieves without opening the 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?

'Useful when an agent needs local temperature, a forecast or active alerts for a US location' gives concrete triggering contexts. There is no explicit when-not guidance or routing to an alternative (e.g. the sibling climate_day for non-NWS or non-US/point-based climate queries), which keeps it short of a 5.

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