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

Annotations already declare readOnly, idempotent, non-destructive, so the safety bar is met structurally. The description adds genuine behavioral context beyond that: it warns that values come from a single year named per layer rather than a multi-year normal, and that each value carries its source, year, unit, licence and cell size, which preempts misreading the data as climatological normals.

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?

The purpose is front-loaded in the first clause, which is good. However, the second sentence is a long noun cascade listing every data layer, which is informative for scope but reads as a dense inventory rather than tight structure. Appropriately sized overall, but not maximally economical.

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?

An output schema exists, so return format needn't be explained, and annotations cover the safety profile. The description is thorough on data scope. The main remaining gap is the absence of routing guidance against sibling tools, but for a read-only lookup tool with a rich output schema this is fairly complete.

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 the schema already documents place, latitude, longitude, and categories. The description adds no syntax, format, or resolution guidance for these parameters (it never clarifies the place-vs-coordinates precedence or the effect of the categories filter). Baseline 3 applies 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 verb+resource ('Long-term climate exposure at a place') and then enumerates exactly which layers are returned (ERA5, CMIP6 projections, sea level rise, flood depth, water stress, drought, aridity, land cover, etc.), so an agent knows precisely what it gets. It does not, however, explicitly distinguish itself from siblings like assess_place, get_forecast, or get_hazards_near, leaving the boundary to inference.

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?

There is no explicit when-to-use statement and no named alternative. The agent must infer that 'long-term' implies use when a historical/projected climate profile is wanted rather than a short-term forecast, but nothing in the text says so or excludes competing tools. This is a clear guidance gap for a tool sitting among six siblings.

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