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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds genuinely new behavioral facts: data source (Defra UK-AIR), that only the nearest *working* monitor is used, the representativeness caveat ('one monitor may not represent your street'), the not-a-forecast limitation, and a per-call cost of 1 credit. These are the constraints an agent needs before committing a call, and none are inferable from the annotations.

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-loaded with the core result and the data source, then caveats and cost at the end where they belong. The parenthetical list (smoke, wood burners, traffic, bonfire night) is slightly decorative, but it earns its place by justifying the health-use framing in the same sentence.

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?

With no output schema, the description carries return-value disclosure and does it well: hourly reading with units, 24-hour mean, DAQI band and health advice. The main omission is what happens when no monitor exists within max_km (error vs. empty), which matters given the 'nearest working monitor' framing.

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 all three parameters (lat, lon, max_km) carry ranges and defaults in the schema. The description reinforces that the search is 'nearest working monitor', but adds no syntax, units, or behavior for max_km exhaustion beyond what the schema states, so the baseline of 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: 'Latest hourly fine particulate (PM2.5) reading in ug/m3 at the nearest working Defra AURN monitor', plus the 24-hour mean and DAQI band returned alongside it. The pollutant is named explicitly, which cleanly separates it from siblings like no2_level_near, pm10_level_near and air_quality_index_near without needing to open any schema.

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 use context ('suits asthma and COPD sufferers, runners and parents') and an explicit exclusion ('Not a forecast'), which routes agents toward forecast tools when prediction is wanted. It stops short of naming the sibling alternatives (e.g. pm10_level_near, air_quality_index_near) or when a different pollutant would be the better call, so it is clear context rather than full routing.

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