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

Annotations cover the read-only/safe profile, and the description adds substantial context beyond them: upstream sources (Finnish Meteorological Institute plus municipal stations), the WHO 2021 and EU comparison baselines, the multi-year `series` returned alongside latest readings, and the critical sparsity warning (~160 stations, missing pollutants are gaps not clean air). This is exactly the kind of domain behavior an agent cannot infer from structured fields.

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?

Three dense sentences, front-loaded with the verb and resource before the interpretation guidance. Every sentence earns its place, though the final coverage warning is slightly verbose relative to the rest.

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, so the description carries the burden of describing returns, and it does: a verdict with named pollutants, per-pollutant comparison to WHO 2021 and EU limits, multi-year series beside latest values, and explicit gap handling. An agent has everything needed to call and interpret it.

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% and the kind enum already explains that municipality gives the median over its stations while postal area uses the nearest station. The description adds no syntax or format detail beyond the schema for either parameter, so 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+resource (measured annual-mean air quality for PM2.5, PM10, NO₂, O₃) with explicit geographic scope (Finnish postal area or municipality) and data provenance. It is unmistakably distinct from the sibling analytical tools like get_area_report or get_place_stats.

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 clear usage context: use it to answer 'is the air clean in Vantaa?' and get a verdict rather than a number. It also instructs how to interpret coverage gaps ('report that as unmeasured, never as clean'). It stops short of naming a sibling alternative or exclusion condition, so 4 rather than 5.

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