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

Beyond the readOnly/idempotent/openWorld annotations, the description discloses the data source (NOAA/NWS Aviation Weather Center, worldwide), a hard freshness constraint ('Only stations that reported in the last 2 hours are returned') that explains missing results, and a per-call credit cost. These are exactly the operational facts an agent cannot infer from annotations or 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?

Front-loads the purpose, then the decoded fields, then constraints and cost in a single tight paragraph. The field enumeration is long but functional; a slightly shorter list would lose no routing information, so it falls just short of ideal conciseness.

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?

No output schema exists, and the description compensates fully by enumerating the decoded fields (temperature in C/F, dew point, humidity, wind/gusts, visibility, cloud/ceiling, pressure, flight category). Combined with the source, freshness window, and cost, an agent has everything needed to call it and interpret results.

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% and the schema already documents the ICAO code format, the comma-list limit of 10, and fallback tools for unknown codes. The description only reinforces that multiple airports are supported ('one or more airports') without adding format or limit detail, 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 verb and resource ('the latest official METAR observation decoded into...') and enumerates the returned quantities, so an agent knows exactly what it gets. It explicitly distinguishes itself from forecast siblings with 'the actual station reading, not a model forecast', separating it from weather, taf_forecast and metar_history.

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?

Gives a clear usage context ('what is the weather right now at one or more airports') plus an explicit exclusion ('not for flight planning'), which steers planning queries elsewhere. It does not name the specific alternative tool (e.g. taf_forecast or metar_history) for those cases, so the routing is implied 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.