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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds genuine context beyond that: the data source (Atmy Data Hub), the epoch (from 2026-01), that yearly means flag complete years, and that the response includes ranked dirtiest/cleanest months and days. The one miss is that 'whole measurement history' implies a potentially large payload with no note on response size or paging.

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 sentences, no filler, with the data-inventory front-loaded and the use-case framing second. The first sentence is dense with semicolon-chained clauses but every clause carries information an agent needs.

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 five-parameter, zero-required, no-output-schema read tool, the description covers what comes back (monthly PM2.5, weather, yearly means, extremes) well enough that absent an output schema an agent still knows the shape of the answer. The remaining gaps are ambiguity versus sibling tools and no stated behavior when the location resolves to nothing within 50 km.

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%, so lat/lon/city/country/lang semantics, the 50 km nearest-city rule, and the slug formats are already fully documented. The description mentions 'a city' but adds no parameter-level guidance such as how city and lat/lon interact or precedence. Baseline 3 is appropriate when the schema carries the load.

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 names a specific resource and scope: 'the whole measurement history of a city' with monthly PM2.5, weather, yearly means and extremes. It does not, however, distinguish itself from the clearly related siblings get_air_quality and get_air_quality_history, so an agent cannot tell from the text alone which of the three to pick.

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 second sentence implies usage with two example question shapes ('how has the air changed', 'the most polluted month on record'), which is helpful framing. But there is no explicit when-not guidance and no named alternative among get_air_quality / get_air_quality_history, which is the main ambiguity an agent faces here.

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