list_areas

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

With no annotations provided, the description carries the full disclosure burden and does meaningful work: it says the tool returns every geography at a single boundary level, only `id` and `name`, and that `id` must always be paired with the same `country`. It does not cover pagination or error behavior, but the core behavioral contract is clear.

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 main action is front-loaded in the first clause, and every subsequent sentence adds needed context: level defaults, country-specific differences, how to discover valid levels, and how the returned `id` is used downstream. The length is justified because the content is dense and non-redundant.

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 two-parameter enumeration tool with an output schema, the description covers the essential operational context: valid countries, level defaults, the UK exception, and downstream consumers of the returned `id`. It omits details like pagination or whether zero results are possible, but these are minor given the output schema and the explicit scope.

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 0%, so the description must fully explain the parameters, and it does: it names the two allowed `country` values and explains `level` with defaults, a UK-specific exception, and examples of other valid levels. It also connects `level` selection to a dataset's `compatible_levels`, adding meaning far beyond the bare schema.

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 opens with a specific verb-resource pair: 'List every geography at one boundary level, for one country,' which unambiguously identifies the tool's job. It also distinguishes the tool from siblings by noting the returned `id` is consumed by `list_area_datasets`/`get_dataset_for_area`, so an agent can tell it apart from dataset-listing or ranking tools.

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?

It gives concrete selection guidance: `level` defaults to 'county' for Ireland, the UK's primary level is 'lad' rather than 'county', and other per-country levels exist. It also directs users to `list_datasets`' `compatible_levels` to see which levels a stat is published at, but it does not explicitly state when not to use this tool versus each sibling.

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