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

With no annotations, the description carries the full behavioral burden. It helpfully discloses the model provenance (NWS-derived, bias-blended, method labeled), the 168-hour horizon, and the pricing model. But it leaves out response shape details, freshness/latency, error conditions, and whether the bias blend always applies. The provenance and pricing context are genuinely useful additions.

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 description opens with a near-duplicate of itself ('Hourly San Diego weather forecast' then repeats 'Hourly weather forecast for San Diego'). It also embeds infra details (HTTP verb, price, docs URL) that read as boilerplate and dilute the signal. Front-loading is decent but redundancy hurts.

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 2-param read tool with no output schema, the description covers what the tool returns and adds provenance/pricing context. It is incomplete in that it doesn't describe the response structure (fields per hour), how 'method' is labeled, or how the 168-hour claim interacts with the 240 max — gaps an agent should not have to infer.

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%, and the description only mentions 'up to 168 hours out' which partially conflicts with the schema's maximum of 240. It adds no meaning for the 'units' enum or the exact semantics of 'hours'. The agent gets no useful semantic grounding beyond the schema's own constraints.

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?

Clearly states it returns an hourly weather forecast for San Diego (temperature, precipitation probability, wind, up to 168 hours). The city is baked into the endpoint, so there is no coordinate ambiguity. It is less differentiated from the many sibling forecast_* tools (weather_forecast-point, weather_forecast-window_san-diego) since it doesn't explain when this is the right choice.

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?

Description implies usage via 'San Diego coordinates built in' and 'same shape as /v1/forecast/point', which hints at when to prefer this over the generic point endpoint. However, it does not name alternatives or state when-not-to-use it (e.g., vs weather_forecast-window_san-diego, weather_forecast-probabilistic, weather_forecast-point with explicit coordinates).

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