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

With no annotations, the description carries the full behavioral burden and does so unusually well. It discloses the paid cost, the fallback behavior between NOAA/NWS observation and MET Norway model, explicit labeling of data type, bounded SI fields, source provenance, and the upstream HTTP method and URL.

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 is a single dense sentence that front-loads the cost signal and then efficiently covers input, source behavior, output labeling, units, provenance, and upstream details. Every phrase earns its place with no filler or repetition.

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?

Given no output schema and no annotations, the description does a strong job of explaining what is returned: a current weather snapshot labeled as observation or model, with bounded SI fields and source provenance. The main completeness gap is the lack of concrete parameter names or an example showing how to specify the city or coordinates in the body/query.

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?

The schema descriptions are generic wrappers for 'body' and 'query', so the description adds some meaning by specifying city/locality name or exact coordinates as accepted inputs. However, it does not explain how those inputs map to specific body or query fields, which is a meaningful gap for actually invoking the tool correctly.

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 a specific verb and resource: 'Get one current weather snapshot' for a city/locality name or exact coordinates. It also differentiates the tool by specifying the NOAA/NWS or MET Norway source and the explicit observation-versus-model labeling, making it easy to distinguish from sibling forecast and alert weather tools.

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 establishes clear context: this tool is for a single current-weather snapshot, not forecasts or alerts. It does not explicitly name alternative sibling tools or state exclusion conditions, but the 'current weather' framing and source details give adequate guidance for when this tool is appropriate.

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