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

Annotations already declare readOnly, idempotent, open-world, non-destructive behavior, so the safety profile is covered. The description adds the dimension-filtering model and the '*' wildcard semantics, but says nothing about result size, pagination, or what happens when a dimension filter matches nothing.

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 short sentences, front-loaded with the action and resource, with no filler. The example is arguably redundant with the schema examples but stays compact.

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 and rich annotations carry the return-value and safety burden, and the description covers the identifying triple plus filtering. Still missing are practical call details such as expected result volume or behavior on empty matches, which matter for an open-world data fetch.

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 schema already documents every parameter, including the dimensions map with the '*' wildcard. The description's example largely repeats the schema's own example rather than adding new meaning, 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 ('Fetch observations') and resource, and names the required dataset/edition/version hierarchy, which distinguishes it from the listing tools. It does not differentiate itself from siblings like uk_ons_get_dataset or get_version, so it stops short of a 5.

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 description describes how to call it but never when to use it versus uk_ons_get_dataset or get_version, nor any precondition such as needing to resolve edition/version first. Usage is only implied by the call shape.

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