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

Annotations already declare readOnly, idempotent, non-destructive, open-world behavior, so safety is covered. The description adds genuinely new context the annotations lack: the free daily allowance and the $0.002 USDC per-call x402 cost after that, which matters for an agent deciding whether to call repeatedly.

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 tight sentences with no filler; the scope constraint is front-loaded and the pricing caveat follows. 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?

An output schema exists, so return values need not be described. The description covers scope and cost, but leaves the relationship to us-weather__points and the daily-allowance reset window unspecified.

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 100%, with x/y and office each documented, including that office comes 'from the points endpoint'. The description adds no parameter detail beyond that, so the baseline 3 is appropriate.

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 ('Hourly forecast') and scope ('for a grid square'), which separates it from the sibling us-weather__forecast by granularity. It does not explicitly name the sibling or contrast the two, so the distinction rests on the name alone.

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?

There is no when-to-use guidance and no alternatives named; the agent must infer from the name that this is the hourly variant of us-weather__forecast. The only implied prerequisite ('a grid square') is not connected to the us-weather__points tool that supplies office/x/y.

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