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

Annotations already declare read-only, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: the underlying models (ECMWF SEAS5, NOAA CPC in the US), the 35-year local climate baseline with warming trend, and the probabilistic nature of the output. No rate limits or caching behavior are mentioned.

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 packed with concrete output detail, so no sentence is wasted. However it is a single dense run-on sentence with stacked parentheticals, which makes the monthly/date/weekly distinction harder to scan than it needs to be.

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?

There is no output schema, so the description carries the full burden of explaining return values, and it does so thoroughly: monthly probability distributions, expected vs normal highs and lows, wet/snow days, date-specific rain/snow/freeze/hot-day chances, and the 6-week weekly odds. An agent knows what it will get back.

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 every parameter documented including units, date patterns, month counts, elevation and ski-resort spot. The description adds little parameter-level guidance beyond confirming the seasonal/per-date framing, so the baseline 3 applies.

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 (long-range seasonal weather outlook, months ahead) and enumerates exactly what it returns: per-month probability of below/near/above-normal temperature and precipitation, expected highs/lows, wet/snow days, plus a date-specific and 6-week weekly view. The 'months ahead' scope cleanly separates it from short-horizon siblings like point_forecast.

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?

The description implies its use case (planning for a future date or season) and the schema mentions a wedding/race/trip, but it never states when to prefer this over point_forecast or plan_trip, nor any exclusions or prerequisites. Usage is inferable rather than spelled out.

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