epa_uv_index

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

Annotations include readOnlyHint: true, so the safe read-only behavior is already known. The description adds value by providing the UV scale interpretation (0-2 Low, etc.), which helps the agent understand the output semantics beyond the schema.

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?

Three sentences: purpose, UV scale, and health relevance. Front-loaded with the primary action, no wasted words, and the scale is a compact data table.

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?

The tool is simple, with good annotations and full schema. The description provides the UV scale, which effectively communicates the expected output format. No output schema exists, but the description covers what a user/agent needs to know for this forecast tool.

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 detailed explanations for zip, city, and state. The description repeats that location is 'ZIP code or city/state' but adds no new param-specific details. Baseline 3 is appropriate when the schema carries the burden.

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 clearly states the tool 'Get UV index forecast for a U.S. location' with specific location types (ZIP or city/state). This verb+resource combination is unambiguous and differentiates it from weather or environmental siblings like nws_forecast or nrel_solar.

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 provides a clear use case: 'Useful for health recommendations -- high UV correlates with skin cancer risk.' It indicates when this data is relevant, though it does not explicitly name alternatives or exclusions.

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