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

Annotations already declare readOnlyHint and openWorldHint, so safety and open-world nature are covered. The description adds genuinely non-obvious operational context: the data comes from the nearest active monitors, results are ranked, and each call costs $0.005 USDC via x402 — the pricing detail is important for an agent that must decide whether to invoke.

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?

Two tight sentences, front-loaded with what is compared and how results are ordered, followed by the cost caveat. Every clause carries information; nothing is redundant padding.

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?

For a single-parameter, read-only, no-output-schema tool, the description covers scope, metrics returned, ordering, data source, and payment requirement. An agent has everything needed to decide to call it and what to expect back.

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 single parameter already documents '2-8 places separated by |'. The description repeats the 2-8 count but adds no separator syntax, format examples, or behavior for out-of-range inputs, so it does not meaningfully extend 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?

Specific verb (compare) plus resource (air quality), with explicit scope (2-8 cities), enumerated metrics (US AQI, category, PM2.5, PM10, ozone, NO2), and output ordering (cleanest to most polluted). It implicitly distinguishes itself from airquality (single place) and airquality_history (past data) via 'compare' and 'current', but never names a sibling to route the agent explicitly.

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?

Usage is implied by the multi-city framing: use it when you need a side-by-side comparison rather than a single reading. However, there is no explicit when-not guidance and no reference to airquality, airquality_history, or airquality_stations, which are the obvious alternatives for single-location or historical queries.

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