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

Beyond the annotations (readOnly, idempotent, openWorld, non-destructive), the description discloses the data source (MET Norway Locationforecast 2.0), the important caveat that values assume a cloudless sky with real UV lower under cloud, that cloud cover is supplied alongside, the forecast horizon limit, and a 1-credit cost. These are exactly the behavioral traits annotations cannot convey.

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 output contents and use cases are front-loaded, and each sentence carries real information (source, caveat, dependency, cost). It is a single dense paragraph with stacked parentheticals, which slightly hurts scanability but contains no 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?

There is no output schema, so the description must describe return values, and it does (hourly series, daily peak, peak time, WHO band, advice). Combined with the clear-sky caveat, horizon limit and coordinate prerequisite, an agent has everything needed to call and interpret it correctly.

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%, so the baseline is 3; the description goes further by telling the agent that lat/lon are mandatory in practice and where to obtain them from place names, and by tying utc_offset to how 'today' is defined. It adds workflow meaning rather than parameter syntax, which is already in the schema.

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?

The description names a specific verb and resource ('Hourly clear-sky UV index for one day at any point') and enumerates the returned components (peak UV, peak time, WHO exposure band, protection advice). It is clearly distinguishable from siblings like weather, cloud_cover_forecast and sunrise_sunset because it states the clear-sky UV framing and the single-day scope.

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?

It gives concrete use cases ('sun-safety, outdoor work and holiday planning'), a hard limitation ('UV is only given for the first few days of the forecast'), and an explicit prerequisite route naming alternatives: 'for a UK place name or postcode, get coordinates from geocode or postcode_lookup first'. That covers when to use it and how to satisfy its inputs without inference.

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