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

There are no annotations, so the description carries the behavioral burden. It describes the output categories and implies a read-only data lookup, but it does not explicitly state the operation type, units, or any caveats about how the tier or capital-growth impact is computed. It is adequate but not rich.

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?

Two sentences with no filler. The core data content is front-loaded and the sibling differentiation is placed second, making the description efficient and easy to parse.

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 one-parameter data lookup with an output schema present, the description covers the tool's purpose, the main metrics, the tier categories, and the relevant alternative. It does not explain the 'underclass' concept, but that is likely acceptable given the output schema and simple input.

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?

The schema only defines `suburb_name` as a string with no description, so the description's reference to 'the suburb' confirms what the parameter means. However, it does not specify expected format, spelling, or example values, leaving some ambiguity for a single required parameter.

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 identifies the exact data returned: welfare-dependency share, public-housing share, underclass tier (High/Mid/Low), and capital-growth impact. It also distinguishes itself from the sibling cohorts tool by clarifying what that tool serves, so an agent can tell them apart.

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 explicitly routes regional and neighbour rank requests to `/demographics/cohorts`, effectively saying this tool is for the suburb-level tier and impact data. This gives a clear when-to-use/when-not-to-use signal relative to the most similar sibling.

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