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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds genuine value beyond annotations: data freshness cadence (20–60 minutes), data provenance (NOAA Aviation Weather Center), licensing/public-domain status, and the explicit 'no auth required' note. It also lists decoded output fields, giving behavioral detail without contradicting any annotation.

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?

Four tightly scoped sentences, each earning its place: the action, the decoded return fields, the freshness cadence, and the source/auth statement. The description is front-loaded with the verb and resource, and there is zero filler or repetition of schema content.

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 output schema covers return structure, annotations cover the read-only/idempotent safety profile, the schema documents parameter edge cases (station limit, hours_back bounds), and the description covers freshness, source, licensing, and auth. Nothing an agent needs to invoke this tool correctly is missing.

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% — both ids and hours_back carry detailed descriptions with examples ('KJFK,KLAX,EGLL'), validation bounds (1–24), default (1), and usage guidance ('Use 3–6 if a station may not have reported in the last hour'). The description's mention of 'one or more ICAO airport stations' mirrors the ids parameter but adds no new semantic weight. Baseline 3 is appropriate since the schema does the heavy lifting.

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 uses a specific verb ('Fetch') with a concrete resource ('latest METAR... for one or more ICAO airport stations') and expands the acronym for disambiguation. It enumerates the decoded fields returned (temperature, wind, visibility, flight category, raw string), which precisely characterizes the tool's output and distinguishes it from meteorological siblings like TAF-forecast and PIREP 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 is for the latest current conditions ('Data updated every 20–60 minutes') rather than forecasts — but it never names alternatives or states when not to use it. With closely overlapping siblings like aviation.metar.current and checkwx.metar.decoded, explicit routing (e.g., 'use the TAF tool for forecasts') is absent; the usage guidance lives only implicitly in the schema's hours_back description rather than in the tool description.

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